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This paper proposes a service-oriented manufacturing strategy in a two-echelon supply chain with random demand. When there is no inventory for the retailer to meet demand, customers can choose to order products through the retailer and products will be delivered to them by the manufacturer directly in the promised time, and we call this delivery service in service-oriented manufacturing. We employ a Stackelberg game-theoretic model to analyse the procurement quantity and delivery time decisions by the manufacturer as the leader and the retailer as the follower. Using the performance of the pure-manufacturing strategy as a benchmark, our main results follow. First, the equilibrium strategies of the two players are obtained. Clear decision rules are also given. Second, delivery service in service-oriented manufacturing can be an effective way to reduce the holding cost of the retailer. Third, we describe the customer loss caused by waiting and find how the manufacturer influences procurement quantity of the retailer through the decision of delivery time. Finally, delivery service in service-oriented manufacturing cannot always improve the profit of the manufacturer and the retailer. We give guidance for managers to provide it. [ABSTRACT FROM AUTHOR]

We consider a general assembly system that produces variations on a single product. Customers can choose to customize any aspect of the product which corresponds to one or more stages of the assembly system. We assume that demand for the original product and the demand for any customization at any stage are all random with known probability distributions. We model this problem as a multi-echelon inventory management problem. This problem has not been studied before. Allowing for customization at any stage in an assembly system makes this problem significantly more complex than similar problems considered in the past. To solve this problem, we 'split' the assembly line into two parallel assembly lines which we call uncommitted and committed lines. We show that the usual method of reducing the assembly system to a series is not possible in general. We develop a heuristic policy which can be used to then reduce the system into a series system. We also present numerical calculations which highlight the efficacy of the heuristic policy. [ABSTRACT FROM AUTHOR]

We consider a production-inventory system in which the facility produces continuously, switching between two production rates: one faster and one slower than the average demand rate. Demand follows a compound Poisson process, and the size of each demand request is an exponential random variable. Unsatisfied demand is backordered. The production-inventory system is controlled by a two-critical number policy (r, R), whereby production switches from the slower rate to the faster rate when inventory drops below level r and from the faster rate to the slower rate when inventory reaches level R. A fixed cost occurs whenever production switches rates. Our analysis covers two cases: r ≥ 0 and the less studied case of r ≤ 0. We use a level crossing approach to derive the steadystate distribution of the inventory level. Using the steady-state distribution of the inventory level, we calculate the total expected inventory holding, backorder, and switchover costs for each of the two cases. We outline how to obtain the optimal policy through a search of the expected cost functions. We also propose heuristics that give simple closed-form solutions with near-optimal performance. Through a numerical study, we illustrate the importance of considering the r ≤ 0 case. [ABSTRACT FROM AUTHOR]

Scheduling is a complex task due to the need to optimise multiple competing objectives and react to unpredictable events that may occur during production execution. The strategy of predictive-reactive scheduling can be used to reconcile the conflict between the original schedule and the current shop floor situation. This study seeks to present an inventory data-driven predictive-reactive production scheduling model that supports the evolving concepts of the Industry 4.0. Periodically, a machine learning technique provides predictive scheduling considering a best-case scenario according to an established Key Performance Indicator (KPI). Then, material non-availability causes disruptions in production, which triggers the Simulation-Based Optimization (SBO) method to handle these events. Thus, SBO provides a reactive schedule with the best set of priority rules to sequence jobs on each machine according to the data on the shop floor. This model was validated with a real case study using data collected from a metal-mechanical company. Considering the service level KPI, the results showed that the model is able to find a better solution in the compared scenarios. Therefore, even in a dynamic and stochastic scenario, with machine breakdowns, quality problems, raw material delays, and accuracy issues, the model proved efficient in mitigating these variations' effects. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of optimising the network of a Third-Party Logistics (3PL) company, placing emphasis on the distinct characteristics of the 3PL environment. The goal is to minimise the warehousing and distribution costs for both forward and reverse product flows. A new Mixed Integer Linear Program (MILP) model is proposed to address this interesting problem. The related decisions include: selection of (a) warehouse(s) and the related product inventory quantities, (b) product unit loads transported, (c) truck combinations employed to perform the corresponding forward and reverse trips. The model was applied in a case study of a 3PL company to optimise part of its forward supply chain that comprises three warehouses, 23 suppliers and 53 customers. The results obtained were very encouraging, since overall warehousing and distribution costs were lowered by 10.8%. Sensitivity analysis indicated that additional savings may result from optimising warehousing capacities. The main contributions of this work are the inclusiveness of key aspects of the 3PL environment in the proposed model, as well as placing emphasis on warehousing costs and on management of truck capacities. A secondary contribution is the validation of the model's value through a comprehensive case study. [ABSTRACT FROM AUTHOR]

This paper investigates a single-vendor, multiple-buyer coordinated supply chain under stochastic demand. Each buyer implements a continuous review policy, and the shortage quantity is fully back-ordered. The lead time for the first shipment includes setup, production, and transportation times, while the lead time for the remaining shipments includes only transportation time. The production time is a function of production lot and production rate, which are both decision variables, and the setup and transportation times are controllable as well. For each buyer, the safety stock in the first replenishment cycle is not necessarily identical to that in the remaining cycles. Two successive shipments from the vendor to a buyer may have different sizes, and their ratio is a decision variable. The problem is finding the production and inventory replenishment policy, production rate, and lead times that minimise the long-run expected total cost per time unit. We demonstrate properties satisfied by the cost function and develop an optimisation algorithm, whose performance is compared to a benchmark algorithm based on a commercial solver in a numerical experiment. The experiments also investigate the benefits stemming from the proposed model when compared to models reproducing situations that leverage some or any of the controlled factors. [ABSTRACT FROM AUTHOR]

Weight Pressures in Sport—Females (WPS-F) questionnaire measures sport-related pressures that female athletes experience regarding body weight, shape, size, and appearance. In order to examine the psychometric properties of the Greek version of the inventory, two different studies were conducted. In the first study, using a sample (n = 225) of female Greek athletes aged 12–20 years, exploratory factor analysis produced two factors (Factor 1: Pressures From Coaches and Sports About Weight and Factor 2: Pressures Regarding Appearance and Performance) and supported the original factor structure. In the second study, using a different sample (n = 318) of female Greek athletes aged 11–18 years, confirmatory factor analysis provided support for the two-factor structure. Weight Pressures in Sport—Females questionnaire was demonstrated to be a valid and reliable instrument for Greek female athletic populations. Future studies should further test the factorial structure in younger and older athletes and in larger samples. [ABSTRACT FROM AUTHOR]

Background: Innovation in nursing involves applying new knowledge to create novel ideas, methods, or technologies, resulting in higher-quality care and improved patient outcomes. Adequate support for innovation is crucial for progress in nursing. This study aimed to translate the Innovation Support Inventory (ISI-12) into Persian and assess its psychometric properties specifically among clinical nurses. Methods: A methodological cross-sectional study was conducted from September 2022 to July 2023 to evaluate the face, content, and construct validity of the ISI-12. Construct validity was assessed through confirmatory factor analysis (CFA) and convergent and discriminant validity evaluation using data obtained from 321 clinical nurses. The test–retest stability and internal consistency of the ISI-12 were also evaluated to assess its reliability. Results: The Persian version of the ISI-12 validation through confirmatory factor analysis has confirmed its fit with the proposed three-factor model. The ISI-12 demonstrated high reliability, as evidenced by a Cronbach's alpha coefficient (α = 0.969), McDonald's omega coefficient (ω = 0.922), coefficient H (H = 0.979), and mean inter-item correlation (ρ = 0.418). Additionally, the stability of the ISI-12 during two weeks among 40 clinical nurses was found to be excellent, with an ICC of 0.951. Conclusion: The Persian version of the ISI-12 is a valid inventory for evaluating the innovation Support of clinical nurses. [ABSTRACT FROM AUTHOR]

• Estimates of modeled CH 4 emission (E) data for 1,325 U.S. landfills were reviewed. • Operators use two methods to estimate E from landfills with a gas collection system. • First-order decay (FOD) method shows increasing emissions. • Collection efficiency assumption method shows decreasing emissions. • FOD method shows some agreement to remotely sensed national estimates. As part of its commitment to the United Nations Framework Convention on Climate Change, the U.S. annually develops a national estimate of methane emissions from municipal solid waste (MSW) landfills by aggregating activity data from each facility. Since 2010, the U.S. has reported a 20 % decrease in MSW landfill emissions despite a 21 % increase in tons disposed. Operator-submitted data were investigated to understand the causes of this decline. In the U.S., operators of landfills with a gas collection and control system (GCCS) calculate their facility's emissions via two separate approaches – (1) first-order decay (FOD) and (2) collection efficiency assumption (CEA) − and select either result to feed into the annual inventory. The FOD model predicts methane generation proportional to waste disposal and that approach calculated a 19 % increase in total methane generated from 2010 to 2022, whereas generation via the CEA approach decreased by 8.9 %. The amount of measured methane collected has increased 7.5 % for the same years. Discrepancies between the two models' generated methane, assumed gas collection efficiencies, and oxidized methane compound into substantive differences in national estimates. Operators more frequently select the CEA method, which results in decreased national estimates. If only the FOD method was used, U.S. MSW landfill emissions would be 1.3-1.7 times greater than current estimates which is similar to recent extrapolations from remote sensing campaigns in the U.S. Both models contain parameters with large inherent uncertainty. Without measurement methods that continuously quantify both point-source and diffuse emissions, an assessment of either equation's accuracy cannot be made. [ABSTRACT FROM AUTHOR]

This study focused on the challenges posed by the fluctuating demand for COVID-19 vaccines, considering factors such as side effects, religious objections, and absenteeism, which result in the accumulation of excess vaccines. Recognizing the resulting social, economic, and environmental issues, this study investigated the application of a lateral transshipment policy for the management of the inventory of short-term vaccines, considering related unpredictabilities. A discrete event simulation built on foundational principles derived from a mixed-integer linear programming model was employed to explore the dynamics of mRNA-based vaccine distribution among two hospitals based on lateral transshipment and reordering policies. Through the simulation of various scenarios over periods of 1-30 days, transshipment based on the availability policy is employed to determine the quantity of vaccines to be transshipped, constrained to vial amounts, and the (s, S) inventory system for reordering. The results of this study underscore the efficacy of lateral transshipment, particularly in situations where demand discrepancies exist between hospitals, thereby revealing its superiority over non-transshipment strategies within 7 days. [ABSTRACT FROM AUTHOR]

Coastal environments, such as bays, are essential to the development of fishery resources due to their economic and ecological importance. This paper presents an updated checklist of coastal marine fishes as part of a long-term monitoring program in Aratu Bay (2014–2024), Bahia state, eastern Brazil. A total of 109 species belonging to 58 families and 24 orders were cataloged. Five endemic species and ten species listed as at risk according to the IUCN criteria (from Vulnerable onwards) were identified. The Carangidae was the most representative family in terms of species number, followed by Gobiidae and Sciaenidae. The ichthyofauna was dominated by mobile invertebrate feeders and macrocarnivores. Two non-native species were observed in the region: the Muzzled blenny, Omobranchus sewalli and the mud sleeper Butis koilomatodon. Aratu Bay supports a diverse ichthyofauna with diverse trophic guilds and habitats, rendering it an important area for the feeding and development of economically valuable species, including those facing threats. [ABSTRACT FROM AUTHOR]

The Economic Production Quantity (EPQ) plays a crucial role in the manufacturing process. The traditional EPQ model operates under the assumption that Non-Conforming (NC) items are not produced, and the process remains under control. However, real-world scenarios often involve the production of NC products, leading to process deviations. This study introduces a model that optimizes the design of a control chart to incorporate NC products into the EPQ model. The model integrates inventory and quality-related costs to minimize the expected total cost by determining EPQ, sample size, and control limit. The solution methodology employs direct search techniques to solve this problem. The sensitivity analysis results demonstrate the significant cost reduction achieved by the proposed model compared to the classical EPQ model. The numerical examples presented in the study show an average cost reduction of approximately 21 percent, highlighting the potential effectiveness of the model in cost reduction efforts. [ABSTRACT FROM AUTHOR]

This paper studies a continuous-review stochastic replenishment model for a multi-component system with regular and emergency orders. The system consists of N parallel and independent components, each of which has a finite life span. In addition, there is a warehouse with a limited stock of new components. Each broken component is replaced by a new component from the stock. When no component is available, an emergency supply is ordered. The stock is managed according to an ((s , S) , (0 , Q e)) policy, which is a combination of an (s , S) policy for the regular order and a (0 , Q e) policy for the emergency order. The regular order is delivered after an exponentially distributed lead time, whereas the emergency order is delivered immediately. We study three sub-policies for emergency orders, which differ from each other in size and in relation to the regular order. Applying the results from queueing theory and phase-type properties, we derive the optimal thresholds for each sub-policy and then compare the economic benefit of each one. [ABSTRACT FROM AUTHOR]

Past research in operations management and marketing on inventory levels and product variety has predominantly focused on their effects on brand performance indicators, such as sales and market share while overlooking the influence on consumers' perceptions of brands. Brand perceptions, encompassing reputation, quality, credibility, and emotional associations, go beyond typical revenue metrics and offer foresight into a brand's future performance. Hence, understanding the effects of inventory and product variety on brand perceptions is crucial, and that constitutes the main contribution of this paper. Through a consumer-facing automobile search platform, we collect data on new cars' inventories of more than 20,000 dealerships in the United States from August 2020 to March 2021. We measure brand perceptions using 273,991 responses by in-market consumers collected by YouGov. To address endogeneity concerns, we model the effects of inventory and variety on perceived brand strength using three different empirical approaches: (1) High-dimensional fixed effects, (2) instrumental variables, and (3) causal forest. Across all analyses, we find that inventory has a positive effect on perceived brand strength but the main effect of product variety is not significant. Our second contribution is related to the fact that past research on inventory and variety does not, for the most part, investigate systematic heterogeneity due to brand- or consumer-specific factors that impact the effectiveness of inventory or variety; to help fill this gap in the literature, we investigate the role of two important and theoretically motivated moderators: Consumer income and luxury status of the brand. We find that consumers' income levels and brands' luxury status negatively (positively) moderate the effects of product inventory (variety) on perceived brand strength. Our results have managerial implications for effective assortment planning under scarcity, determining the right range of product offerings for luxury versus nonluxury brands, optimizing the customer's online browsing experience, and targeting advertisements based on brand and consumer characteristics. [ABSTRACT FROM AUTHOR]

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic. [ABSTRACT FROM AUTHOR]

This study examined the potential of mangrove ecotourism in Siak District, Indonesia, as an ethnobotanical research center that integrates traditional medicinal plant use with environmental preservation. Through field studies that included environmental quality monitoring, vegetation and fauna identification, and interviews with local communities, this study showed that the area has high biodiversity and potential for ethnobotanical development. There were 11 mangrove species and 28 faunal species, including protected and endangered species. In addition to being ecotourism objects, mangroves have also been identified as a potential source of traditional medicinal plants, with seven species being utilized by the local community. The various phytochemical components of mangroves provide a wide range of therapeutic effects, including antibacterial, antioxidant, and antitumor effects. Accordingly, the Sungai Bersejarah Siak mangrove ecotourism area promises sustainable development that integrates aspects of environmental conservation, tourist attractions, and the utilization of ethnobotanical potential to improve public health. [ABSTRACT FROM AUTHOR]

Inventory Projection and Asymptotic Optimality van Jaarsveld and Arts propose a new policy for the canonical periodic review lost sales inventory problem. Under this policy, orders are placed in each period such that the expected inventory level at the moment of replenishment order arrival is at a fixed level. This single-parameter policy is called the projected inventory-level (PIL) policy. The PIL inherits asymptotic optimality properties from the constant-order policy for long lead time and from the base-stock policy when the cost of losing a sale is large. The PIL policy has lower cost than competing heuristics in a numerical study. The PIL seems to be a promising approach for other inventory systems with a high-dimensional state space, such as the perishable item inventory management problem. We consider the canonical periodic review lost sales inventory system with positive lead times and stochastic i.i.d. demand under the average cost criterion. We introduce a new policy that places orders such that the expected inventory level at the time of arrival of an order is at a fixed level and call it the projected inventory-level policy. We prove that this policy has a cost rate superior to the equivalent system where excess demand is back-ordered instead of lost and therefore, is asymptotically optimal as the cost of losing a sale approaches infinity under mild distributional assumptions. We further show that this policy dominates the constant-order policy for any finite lead time and therefore, is asymptotically optimal as the lead time approaches infinity for the case of exponentially distributed demand per period. Numerical results show that this policy also performs superior relative to other policies. Funding: This work was supported by the Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Grant 451-16-025]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/opre.2021.0032. [ABSTRACT FROM AUTHOR]

The geoconservation policies assumed by the Sicilian Region (Italy) induced to classify as geosites all the geodiversity preserved in the Sicilian natural reserves. In particular, two of these geosites present in the oriented natural reserve of the coastal lagoon of Cape Peloro (Messina, NE Sicily, Italy), denoted "Morpho–tectonic system of Cape Peloro–Lake Faro" and "Morpho–tectonic system of Cape Peloro–Lake Ganzirri", were considered Global areal geosites on the base of their tectonic origin. Lacking an official scientific report of these sites, the present research was aimed to investigate the lagoon, in order to provide the (i) geological and structural framework, (ii) inventory, and (iii) quantitative assessment of geodiversity. The study geosites resulted to be originated during the post–Wurmian sea–level rise and the strong extensional tectonics affecting the Calabria–Peloritani Arc still active. Indeed, the lagoon depression hosting the Lakes Faro and Ganzirri, developed on low-relief coasts because of different systems of capable faults, NW–SE oriented in the Lake Faro and ENE–WSW oriented in the Lake Ganzirri. The quantitative assessment of geodiversity indicated high scores for the scientific value and the potential educational and touristic uses. On the basis of these results, it was possible to confirm the attribution of Lake Faro's and Lake Ganzirri's geodiversity to Global areal geosites, being the study morpho-structures key localities, providing indicators of representativeness, geological diversity, and rarity that ought to be protected as clear and unequivocal examples of the Earth's geological history and evolution of the Quaternary tectonic coastal lagoons. Actual criticisms that could irreversibly affect the environmental equilibria have been evidenced. Possible actions for the redevelopment of the oriented natural reserve of the coastal lagoon of Cape Peloro and the extension of the geosites were also described. [ABSTRACT FROM AUTHOR]

This paper makes an attempt to develop a periodic review inventory system with imperfect quality of items. In this system, there are two resupply modes, namely regular mode and emergency supply mode. After reviewing the rest quantity at the review epoch decisions are taken that which supply mode should be used. And hence, the order is placed. Regular supply case has a higher lead time and shorter ordering cost compared to emergency supply case. Items are received with imperfectness which is random. After receiving the items, an immediate screening process has been started and imperfect items are separated. This problem is analyzed through the order-up-to R H inventory control system framework. Hence, there must be suitable units of items that raise the inventory position to R H . In this circumstance, it can be shown that either the regular supply case is used or there is an indifferent inventory position E at the review position such that, a higher quantity than E carries out the regular supply case and a lesser quantity than E carries out emergency supply mode. Thus models are developed and optimized through some analytical methods. Finally, numerical examples are taken and concluded through analytical discussions. [ABSTRACT FROM AUTHOR]

The integer-order methods may fail to adequately describe the behavior of many real-world inventory systems. A fractional order inventory model can be developed to examine the memory effect on the demand. In this article, we develop a fractional order inventory control policy related to non-immediately degrading goods by incorporating memory and selling price sensitive demand. The mathematical model is developed using Caputo fractional derivatives and analyzed using Laplace transform approach. An appropriate preservation policy is established to reduce the degradation in the inventory system. It is evident from the literature that the advanced payment schemes for memory-based inventory systems have not been investigated. A partial pre-payment plan where the vendor provides a discount on the purchasing price is studied by considering memory-based demand. Particle swarm optimization and differential evolution metaheuristics are employed to handle the profit maximization problem. The usefulness of the memory-based model is examined by taking a numerical example. The proposed study also reveals that the memory indices significantly impact the optimal profit. Management insights are established by considering the model's applicability by taking numerical illustrations and performing sensitivity tests on the key inventory parameters. [ABSTRACT FROM AUTHOR]

Carbon emissions are a major contributor to global warming and climate change. The government has adopted carbon tax (CT) and cap-and-trade policies to reduce carbon emissions from carbon companies. This paper develops a production–inventory model for scarce perishable goods under different carbon policies and outside green technology. This study covers the contribution of energy-efficient green technology in a multi-stage supply chain to control carbon emissions in producing and transporting goods from the manufacturer to the dealer. However, it discusses a different combination of carbon policies chosen for manufacturers and retailers in their countries. According to the findings, changes in carbon pricing, CT, and exchange rates under various policy combinations have varying effects on the entire supply chain, each member's interests, and the social benefits of reducing carbon emissions. It seeks to provide useful information to decision-makers in businesses or supply chains, especially multinational corporations, to make decisions related to fixed rate CT and cap partial deficit cases, long cycle time, reasonable profit with small value, and long term and low cost of green technology investment. The main objective is to find the best material sourcing, production, and distribution strategy for manufacturers and the best replenishment strategy for retailers to maximize the overall joint profitability of the supply chain. In summary, sensitivity analysis has provided an optimal solution management implication based on certain key parameters and CT size. [ABSTRACT FROM AUTHOR]

Vendor credit line ( VCL ) is a common instrument to fund retailers with capital constraints, wherein a supplier extends credit for a retailer's purchases and limits credit size for the sake of default risk. Our study investigates the operational and financial decisions in a supply chain consisting of a supplier and a capital-constrained retailer, wherein the supplier sets credit limits for the retailer's ordering, and then examines the financing choice between VCL and bank loan. We derive the equilibrium credit limits, order quantity and financing mode and conclude that, the credit limits linearly increase with the capital level, and both credit limits and capital level are decisive to the order quantity and financing mode. In the illustrating examples, we identify the decision regions contingent on critical fractiles under different demand distributions (e.g., normal, uniform and exponential) and find the financing choice hinging on the supplier's profit margin if the capital level stays low, otherwise VCL dominates. Finally, sensitivity analysis on key parameters is employed, suggesting that VCL is more preferable as the wholesale price increases or as the retail price and production cost decreases. [ABSTRACT FROM AUTHOR]

Motivated by a long-standing gap between inventory theory and practice, we study online inventory models with unknown cyclic demand distributions. We design provably efficient reinforcement learning (RL) algorithms that leverage the structure of inventory problems to achieve optimal theoretical guarantees that surpass existing results. We apply the standard performance measure in online learning literature, regret, which is defined as the difference between the total expected cost of our policy and the total expected cost of the clairvoyant optimal policy that has full knowledge of the demand distributions a priori. This paper analyzes, in the presence of unknown cyclic demands, both the lost-sales model with zero lead time and the multiproduct backlogging model with positive lead times, fixed joint-ordering costs and order limits. For both models, we first introduce episodic models where inventory is discarded at the end of every cycle, and then build upon these results to analyze the nondiscarding models. Our RL policies HQL and FQL achieve O˜(T) regret for the episodic lost-sales model and the episodic multiproduct backlogging model, matching the regret lower bound that we prove in this paper. For the nondiscarding models, we construct a bandit learning algorithm on top that governs multiple copies of the previous RL algorithms, named Meta-HQL. Meta-HQL achieves O˜(T) regret for the nondiscarding lost-sales model with zero lead time, again matching the regret lower bound. For the nondiscarding multiproduct backlogging model, our policy Mimic-QL achieves O˜(T5/6) regret. Our policies remove the regret dependence on the cardinality of the state-action space for inventory problems, which is an improvement over existing RL algorithms. We conducted experiments with a real sales data set from Rossmann, one of the largest drugstore chains in Europe, and also with a synthetic data set. For both sets of experiments, our policy converges rapidly to the optimal policy and dramatically outperforms the best policy that models demand as independent and identically distributed instead of cyclic. This paper was accepted by J. George Shanthikumar, data science. Funding: X.-Y. Gong was partially supported by an Accenture Fellowship. The work of X.-Y. Gong and D. Simchi-Levi was partially supported by the MIT Data Science Lab. Supplemental Material: The data and online appendices are available at https://doi.org/10.1287/mnsc.2023.4947. [ABSTRACT FROM AUTHOR]

An inventory and assessment of mountainous geoheritage sites based on solid and clear criteria is a first step for any geoconservation strategy. The study area (DPR Korea) has a complex geological setting and many mountains with geological significance, the reasons that justify the mountainous geoheritage inventory done in this work. The inventoried ten mountainous geoheritage sites were quantitatively assessed and clearly show that Mt. Paektu and Mt. Kumgang is the most important mountainous geoheritage sites in the DPR Korea due to its high international scientific value. Mt. Chilbo and Mt. Myohyang have a slightly low value than these geoheritage sites in scientific value, but a high educational value and a high touristic value. In addition, the majority of the other mountainous geoheritage sites are characterized by moderate scientific, high educational, and high touristic values and low degradation risk. This study may help in selecting the ranking of mountainous geoheritage sites for World Heritage registration and the development of a new geopark project in DPR Korea, a country where the geopark concept is still emerging. [ABSTRACT FROM AUTHOR]

Background: Forests are significant terrestrial biomes for carbon storage, and annual carbon accumulation of forest biomass contributes offsets affecting net greenhouse gases in the atmosphere. The immediate loss of stored carbon through fire on forest lands reduces the annual offsets provided by forests. As such, the United States reporting includes annual estimates of direct fire emissions in conjunction with the overall forest stock and change estimates as a part of national greenhouse gas inventories within the United Nations Framework Convention on Climate Change. Forest fire emissions reported for the United States, such as the 129 Tg CO2 reported for 2022, are based on the Wildland Fire Emissions Inventory System (WFEIS). Current WFEIS estimates are included in the Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2022 published in 2024 by the United States Environmental Protection Agency. Here, we describe WFEIS the fire emissions inventory system we used to address current information needs, and an analysis to confirm compatibility of carbon mass between estimated forest fire emissions and carbon in forest stocks. Results: The summaries of emissions from forests are consistent with previous reports that show rates and interannual variability in emissions and forest land area burned are generally greater in recent years relative to the 1990s. Both emissions and interannual variability are greater in the western United States. The years with the highest CO2 emissions from forest fires on the 48 conterminous states plus Alaska were 2004, 2005, and 2015. In some years, Alaska emissions exceed those of the 48 conterminous states, such as in 2022, for example. Comparison of forest fire emission to forest carbon stocks indicate there is unlikely any serious disconnect between inventory and fire emissions estimates. Conclusions: The WFEIS system is a user-driven approach made available via a web browser. Model results are compatible with the scope and reporting needs of the annual national greenhouse gas inventories. [ABSTRACT FROM AUTHOR]

Arming at the coexistence dilemma of inventory overhang and shortage of different maintenance equipment supply nodes, a steady-state coefficient of a supply node has been described with which contains inventory level, the support degree between nodes each other, the demand status of the area guaranteed by the node and the cost of risk when the demand cannot be met. The steady-state coefficient of the inventory network was calculated on the base of all of support nodes. The active adustment is carried out flowing the corresponding algorithm according to the gap between the steady-state coefficient and the threshold which has been set before. The scientific, automatic and intelligent level of equipment adjustment can be greatly improved, consequently the success rate of maintenance support is improved if the passive stock adjustment is combined be- cause of out of stock at the same time. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a sustainable inventory model with a learning effect for imperfect quality items under different kinds of fuzzy environments like crisp, general fuzzy, cloudy fuzzy, and monsoon fuzzy. We divided the mathematical model into three parts under the learning effect according to the real-time fuzzy components (crisp, cloudy, and monsoon environments) of the demand rate of the items. We minimized the total inventory cost with respect to cycle length in each environment under the proposed assumptions. The non-linear optimization technique is applied for the algorithm and the solution method to find the decision variable. Finally, we compared the total inventory cost under different fuzzy environments and our finding is that the fuzzy monsoon environment is a more effective fuzzy environment than crisp and cloudy fuzzy environments. We have presented a numerical example for the validation of the proposed model and have shown the impact of the inventory input parameters on the cycle length and total inventory fuzzy cost. The managerial insights and future scope of this proposed study have been shown in the sensitivity analysis and conclusion. The limitations, application, future extension and scope, and social implementation have been shown in this research study. [ABSTRACT FROM AUTHOR]

Singapore has established six Integrated Construction and Prefabrication Hubs with the goal of meeting ambitious productivity targets and building a resilient precast supply chain by 2024. These factories are equipped with high levels of mechanization and automation. However, they are currently operating far below their designed capacity due to a storage bottleneck. In land-scarce Singapore, finding large spaces for precast storage is a challenge. One possible solution is to implement a just-in-time approach. To achieve this, a systematic approach is required to plan, monitor, and control the entire supply chain effectively, utilizing various strategies, methods, and tools. This paper aims to conduct a comprehensive literature review in related areas, believing that knowledge transfer is a faster way to develop solutions to new problems. The main idea of the proposed solution is to implement an integrated supply chain system model with a central decision-maker. It is recommended that the factories take a more active role in decision-making. Establishing this integrated system relies on trust and information sharing, which can be facilitated by cutting-edge digital technologies. The results of this paper will provide valuable insights for future research aimed at completely solving this issue. [ABSTRACT FROM AUTHOR]

At the University of Nebraska Medical Center College of Pharmacy, a longitudinal project is underway to assess how the college is functioning in terms of keeping Justice, Equity, Diversity, and Inclusion (JEDI) at the forefront of the institution. This study is intended to showcase areas of excellence within the college and as a quality improvement exercise to show the institution potential areas in need of improvement. This process was also initiated because such assessments may soon become a requirement for colleges of pharmacy to earn full accreditation. Upon analyzing the Justice component of JEDI and the 32 justice-related ideas that were recommended for exploration and discussion, and further sub-categorized under the terms representation, curriculum and education, policies and procedures, support and resources, and college climate, useful data were discovered. Overall, the information found on representation, policy and procedure, and college climate was difficult to quantify as much of the information was subjective; however, this does not automatically discount this information from being useful. Information relating to curriculum and education was more quantifiable but may be underrepresented. Analyzing information found relating to resources was made possible by identifying readily available support offered at the college for faculty, staff, and students. In identifying these resources, the college was able to take note of any missing support that needed to be implemented to ensure justice was being maintained. This longitudinal process not only allows the college to see areas where they thrive, but it also highlights any shortcomings of the college while providing the institution with information to spark innovative ideas to strengthen and further promote justice. [ABSTRACT FROM AUTHOR]

Any industry needs sustainability to survive in today's competitive business world. An eco-friendly production system conserves natural resources and protects the planet. Eco-friendly products use sustainable materials and have a flexible production rate, reducing business costs while helping the environment. Considering this scenario, the present paper introduces an investment in the production system to reduce carbon emissions. Further, the demand for the product, as well as the selling price of the product, is dependent on the investment in the advertisement and the additional investment in the production system. Moreover, the production rate is flexible as demand fluctuates, and carbon emissions are reflected too. This research aims to build a model that can optimize production rates, incorporate investments in environmentally friendly production, and maximize total profit while reducing carbon emissions. Businesses need a solid framework to handle the intricacies of sustainable manufacturing and marketing in today's competitive marketplace, and this study intends to give just that by tackling these interrelated factors. A numerical example is illustrated to support the features of the model. [ABSTRACT FROM AUTHOR]

Increasing strict carbon regulations enforced by regulators are encouraging companies to seek better ways to manage inventories with a desire to reduce carbon emissions from their operations. This work illustrates an inventory model to obtain the retailer's optimal replenishment policy for non-instantaneous deteriorating items with fixed lifetime and partial backordering under cap-and-price, cap-and-trade, and carbon tax regulations with the goal of maximizing a retailer's profit while simultaneously reducing total carbon emissions. To investigate the work from a more general perspective, the market demand structure of perishable products is considered deterministic in nature and is reliant on both the selling price and stock level, while the shortage of items is a decreasing function of waiting time up to the next replenishment. This study examines, for the first time, the best replenishment decisions for non-instantaneous deteriorating items with an expiration date after characterizing their properties theoretically under carbon regulations. Integrating all possible cases of the optimal solutions from theoretical outcomes, different numerical examples are demonstrated, and finally, several management insights are provided by investigating the changing pattern of the optimal strategies for variation in the system parameters. The derived outcomes highlight that the cap-and-price policy performs well both economically and environmentally for the inventory decision-maker when the penalty is less than or equal to the reward for each unit of carbon emission. Furthermore, in cap-and-price regulation, the total profit is increased by 3.14 % , 8.10 % , and 1.63 % from cap-and-trade, carbon tax, and without carbon regulation, respectively, and the total amount of emission is decreased by 5.38% from cap-and-trade and carbon tax regulation. [ABSTRACT FROM AUTHOR]

We present the updated checklist of the alien flora of Mongolia, with information on species status, taxonomy, distribution, habitats, and economic use. In total, we recorded 154 taxa of alien plants, of which 33 are naturalized and 121 are casual. The alien flora belongs to 32 families, with Amaranthaceae, Fabaceae, and Brassicaceae containing most of the naturalized species and Asteraceae and Poaceae being the richest in casuals. Annuals (101 species) and perennials (27 species) are the most common life forms among the alien species of Mongolia, while woody and aquatic are only represented by two species and parasitic by one species. The majority of Mongolian alien plants originate from temperate Asia (81 species), Europe (72 species), and Africa (53 species). Alien species are restricted to a relatively narrow range of habitats, all heavily transformed by humans, with 42.2% of all species recorded in agricultural habitats. Regarding economic use, food plants dominate, while those used as fodder show the greatest naturalization success. The 29 most widespread naturalized alien species were recorded in all 22 provinces. Compared to other countries in temperate Asia, the Mongolian alien flora is relatively poor, which can be attributed to harsh climatic conditions and the country's isolation in the past. Our study provides the first step toward a science-based approach to plant invasions by policymakers, authorities, and managers in Mongolia. [ABSTRACT FROM AUTHOR]

Cryptocurrencies are digital currencies void of any support from regulatory body that is currently in vogue as a medium of exchange and an investment security. This paper examines the accounting treatment for cryptocurrency from the perspective of IFRS and AAOIFI accounting standards and propose actions to standard setters on the best way to treat the Crypto transactions in accounting reports. A proper accounting treatment will allow for a fair reporting of crypto related transactions and facilitate users of financial statements to make objective assessment of this new invention. A content analysis was conducted to review all major accounting standards issued by accounting standards setting bodies for possible accounting treatment for cryptocurrencies. To better understand the issue in practice, an analysis of accounting treatment of cryptocurrencies by 2 companies also was conducted. This study found that there is no suitable accounting standard that could objectively be applied for cryptocurrencies. For example, from the perspective of the current accounting standards, cryptocurrencies match the definition of inventory if it is used as a commodity for broker-trader and intangible asset for others respectively. It is suggested that there an urgent need for the International Accounting Standards Board (IASB) to comprehensively develop accounting standard for cryptocurrency, specifically to develop a specific category for this type of assets to allow a standard treatment for cryptocurrency and fill the gap in the IFRS. [ABSTRACT FROM AUTHOR]

The methods and result of scientific studies are often difficult to understand for non-specialists due to their esoteric nature. Such lack of understanding means that such work is removed from our normal life experience, and thus, the applicability, interest and use of such work can be minimal. The communication of geoscience finds a natural conduit through geoheritage. A good example of an inaccessible technique far removed from everyday experience is anisotropy of magnetic susceptibility (AMS), an extremely useful geoscience technique with many applications, including finding strain and flow directions in rocks. We explored here how to make “AMS” understandable, using three different volcanic sites where the flow of molten rock is an important aspect, each situated in different types of geoheritage visitation context (wild trekkers, beach visitors, and walkers). The method we developed and tested follows the production of simple and adapted explanations, and is coupled with geoheritage inventorying and communication. We utilized the tangible geological features of outcrops, as well as intangible elements such as rock magnetic data, and conducted a geoheritage inventory using the modified geosite assessment model (M-GAM) to create narratives for popular comprehension. The M-GAM analysis has identified the geosites of the San Bartolo lava flow of the Stromboli volcano for the communication of AMS. Later, a simple and comprehensible definition of AMS and thus of the flow processes was created using a step-by-step process. This method could be useful for scientific studies to allow them to reach out to a wider public, using their input in the simple explanation stage to con-construct a narrative. This would provide a way for science to be more widely appreciated, useful and applicable.

Abstract Background Innovation in nursing involves applying new knowledge to create novel ideas, methods, or technologies, resulting in higher-quality care and improved patient outcomes. Adequate support for innovation is crucial for progress in nursing. This study aimed to translate the Innovation Support Inventory (ISI-12) into Persian and assess its psychometric properties specifically among clinical nurses. Methods A methodological cross-sectional study was conducted from September 2022 to July 2023 to evaluate the face, content, and construct validity of the ISI-12. Construct validity was assessed through confirmatory factor analysis (CFA) and convergent and discriminant validity evaluation using data obtained from 321 clinical nurses. The test–retest stability and internal consistency of the ISI-12 were also evaluated to assess its reliability. Results The Persian version of the ISI-12 validation through confirmatory factor analysis has confirmed its fit with the proposed three-factor model. The ISI-12 demonstrated high reliability, as evidenced by a Cronbach's alpha coefficient (α = 0.969), McDonald's omega coefficient (ω = 0.922), coefficient H (H = 0.979), and mean inter-item correlation (ρ = 0.418). Additionally, the stability of the ISI-12 during two weeks among 40 clinical nurses was found to be excellent, with an ICC of 0.951. Conclusion The Persian version of the ISI-12 is a valid inventory for evaluating the innovation Support of clinical nurses.

Abstract This study focused on the challenges posed by the fluctuating demand for COVID-19 vaccines, considering factors such as side effects, religious objections, and absenteeism, which result in the accumulation of excess vaccines. Recognizing the resulting social, economic, and environmental issues, this study investigated the application of a lateral transshipment policy for the management of the inventory of short-term vaccines, considering related unpredictabilities. A discrete event simulation built on foundational principles derived from a mixed-integer linear programming model was employed to explore the dynamics of mRNA-based vaccine distribution among two hospitals based on lateral transshipment and reordering policies. Through the simulation of various scenarios over periods of 1-30 days, transshipment based on the availability policy is employed to determine the quantity of vaccines to be transshipped, constrained to vial amounts, and the (s, S) inventory system for reordering. The results of this study underscore the efficacy of lateral transshipment, particularly in situations where demand discrepancies exist between hospitals, thereby revealing its superiority over non-transshipment strategies within 7 days.

Inventory management is an indispensable element of the firm's operational efficiency that determines the results of its activity and its long-term performance. The present study aims to analyze the influence of efficient inventory management on the performance of firms in the Wholesale and Retail trade sector, trying to isolate this relationship in order to bring out as many peculiarities as possible. In order to achieve the aim, fixed effects panel linear regression analysis was undertaken, applying the least squares dummy variables method. The regression models were constructed separately for the dependent variables of Gross Margin and Gross operating surplus as proxies for performance, and separately for the three datasets: Wholesale and Retail trade, Wholesale trade and Retail trade. The results of the analysis reveal the existence of significant relationships between inventory management and firm performance. The significant relationships identified did not confirm the expectations, although were validated by previous results identified in the literature.

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

Abstract Background Forests are significant terrestrial biomes for carbon storage, and annual carbon accumulation of forest biomass contributes offsets affecting net greenhouse gases in the atmosphere. The immediate loss of stored carbon through fire on forest lands reduces the annual offsets provided by forests. As such, the United States reporting includes annual estimates of direct fire emissions in conjunction with the overall forest stock and change estimates as a part of national greenhouse gas inventories within the United Nations Framework Convention on Climate Change. Forest fire emissions reported for the United States, such as the 129 Tg CO2 reported for 2022, are based on the Wildland Fire Emissions Inventory System (WFEIS). Current WFEIS estimates are included in the Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2022 published in 2024 by the United States Environmental Protection Agency. Here, we describe WFEIS the fire emissions inventory system we used to address current information needs, and an analysis to confirm compatibility of carbon mass between estimated forest fire emissions and carbon in forest stocks. Results The summaries of emissions from forests are consistent with previous reports that show rates and interannual variability in emissions and forest land area burned are generally greater in recent years relative to the 1990s. Both emissions and interannual variability are greater in the western United States. The years with the highest CO2 emissions from forest fires on the 48 conterminous states plus Alaska were 2004, 2005, and 2015. In some years, Alaska emissions exceed those of the 48 conterminous states, such as in 2022, for example. Comparison of forest fire emission to forest carbon stocks indicate there is unlikely any serious disconnect between inventory and fire emissions estimates. Conclusions The WFEIS system is a user-driven approach made available via a web browser. Model results are compatible with the scope and reporting needs of the annual national greenhouse gas inventories.

Arming at the coexistence dilemma of inventory overhang and shortage of different maintenance equipment supply nodes, a steady-state coefficient of a supply node has been described with which contains inventory level, the support degree between nodes each other, the demand status of the area guaranteed by the node and the cost of risk when the demand cannot be met. The steady-state coefficient of the inventory network was calculated on the base of all of support nodes. The active adjustment is carried out flowing the corresponding algorithm according to the gap between the steady-state coefficient and the threshold which has been set before. The scientific, automatic and intelligent level of equipment adjustment can be greatly improved, consequently the success rate of maintenance support is improved if the passive stock adjustment is combined because of out of stock at the same time.

Los Angeles is a major hotspot for ozone and particulate matter air pollution in the United States. Ozone and PM2.5 in this region have not improved substantially for the past decade, despite a reduction in vehicular emissions of their precursors, NOx and volatile organic compounds (VOCs). This reduction in traditional sources has made the current emission mixture of air pollutant precursors more uncertain. To map and quantify emissions of a wide range of VOCs in this urban area, we performed airborne eddy covariance measurements with wavelet analysis. VOC fluxes measured include tracers for source categories, such as traffic, vegetation, and volatile chemical products (VCPs). Mass fluxes were dominated by oxygenated VOCs, with ethanol contributing ∼29% of the total. In terms of OH reactivity and aerosol formation potential, terpenoids contributed more than half. Observed fluxes were compared with two commonly used emission inventories: the California Air Resources Board inventory and the combination of the Biogenic Emission Inventory System with the Fuel-based Inventory of Vehicle Emissions combined with Volatile Chemical Products (FIVE-VCP). The comparison shows mismatches regarding the amount, spatial distribution, and weekend effects of observed VOC emissions with the inventories. The agreement was best for typical transportation related VOCs, while discrepancies were larger for biogenic and VCP-related VOCs.

With an increase in market competition, the association between marketing and inventory management has become more important. The commercial activities are more rapid through social media, and advertising has played a crucial role in reaching the product to the consumers before it hits the market. It has thus become normal in an oligopolistic marketing system to increase sales through advertising effort and gain more profit from potential market. It is challenging, nevertheless, to calculate demand and costs related to advertising efforts. As a result, the purpose of this study is to identify the best advertising approach and its potential impact on demand in order to optimize the firm's overall profit. In this paper, we develop an inventory model for deteriorating items to obtain an optimal advertising and inventory strategy, where the consumer demand rate depends on advertising effort and inventory of the items displayed in the store. We have formulated two optimal control problems with the assumption that the replenishment cycle is longer than the fresh product time or not. It is assumed that products do not decay within the fresh product time interval, and inventory decreases due to consumer demand. Next, items will deteriorate and inventory level decreases because of the combined effects of customer demand and deterioration. The analytical solution for the optimal dynamic advertising effort strategies obtained by applying Pontryagin’s maximum principle to maximize overall profit over the planning period. The efficiency of the proposed model is demonstrated by numerical examples. A parameter sensitivity analysis is also performed, providing suggestions for enhancing the firm's profitability when dealing with deteriorating products.

In this study, an inventory of 58 karst collapse dolines within the Sahel-Doukkala, region of Morocco, was conducted from 2018 to 2020. The inventoried data include geological and geomorphological information. Data acquisition methods involved aerial and satellite imagery and field surveys. The karst collapse dolines exhibit distinct features delineating two zones with differing collapse mechanisms. In the Doukkala plain, the formation of collapse dolines is primarily driven by fluctuating water table levels influenced by annual rainfall variations. This impacts underground voids and hydrostatic stability, particularly during seasonal wet-dry cycles. In contrast, collapse dolines in the Sahel zone result from intense rainfall and rapid erosion, enlarging underground voids and triggering collapse phenomena. The analysis of their distribution related to tectonic lineaments shows two main directions: one N-S along the Sahel, corresponding to the region’s fault lines, and another NE-SW in the Doukkala plain, influenced by faults controlling surface flows. This research contributes to understanding the dynamics of karst collapses and aids in developing better management and mitigation strategies for regions prone to such geological hazards. [ABSTRACT FROM AUTHOR]

Retailers are increasingly promising a maximum fulfillment time window for fulfilling customer orders. Motivated by such guarantees, we consider an infinite-horizon periodic-review base-stock inventory system that imposes an endogenously determined fulfillment-time limit for accepted orders. The inventory position is reviewed every fixed T periods and an order is placed to bring the system inventory up to R, the target base stock. The replenishment lead time is a constant of L periods. In each period, the realized consumer demand is accepted only if it can be filled within a guaranteed time limit of τ periods. By incorporating a fulfillment-time limit, the model allows both backorders and lost sales. The objective is to find the strategy that minimizes the long-term average cost per unit time by selecting the base stock and guaranteed-delivery time limit. The behavior of the optimal R with respect to the guaranteed service time τ is investigated, and subsequently, the best value of τ is identified. Interestingly, when τ is greater than or equal to L, the best value of τ is independent of the holding cost and the base stock R. Regularity conditions are developed that assure the cost function is unimodal in R, guaranteeing the optimal base-stock solution can be found easily for a broad family of demand distributions. The solution procedure is extended to the case when the mean customer demand depends on the fulfillment time window promised by the retailer. We find greater customer sensitivity to the fulfillment time leads to a decrease in the optimal fulfillment time guarantee. [ABSTRACT FROM AUTHOR]

We consider a continuous-review inventory control problem for a hybrid manufacturing and remanufacturing system with product recovery and setup costs. A pull policy has been proposed in the literature, however, finding its optimal parameters requires an exhaustive search and a single cost function evaluation is itself complex. We propose a tractable approach to finding these parameters using an interim policy called double (r, Q) with parameters (r m , Q m , r r , Q r) . When the inventory position of the serviceable item reaches rr, a remanufacturing lot size Qr is setup if recoverable inventory is sufficient. Otherwise, we allow the inventory position to decrease further. As it drops to rm, a manufacturing lot size Qm is placed. Unlike the pull policy, this interim policy suspends the remanufacturing option when the inventory position is less than rr. This facilitates an efficient approximation of the recoverable inventory which decouples the double (r, Q) problem into two standard (r, Q) problems. It can then be efficiently solved using a modification of existing (r, Q) algorithms for two instances. Numerical studies show that our approach performs well relative to the optimal pull policy with parameters estimated from an extensive Simulation-Optimization method and other heuristics found in the literature. The approach is also extended to correlated demand and return arrivals. [ABSTRACT FROM AUTHOR]

Two of the major problems Traditional Manufacturing (TM) supply chains face are setting requisite reactive strategies to address the uncertainties in demand and the optimal placement of these buffering capacities in order to be both responsive and cost-effective. With Additive Manufacturing (AM) stepping into large-scale production at different firms, we address the aforementioned supply chain dilemmas by considering the potential role of AM in a TM supply chain network where AM facilities can act as a recourse to the TMs and, also, as a dedicated source providing responsive and cost-effective sourcing alternatives. We develop an analytical allocation rule based on cost differentials, which provides optimal sourcing decisions through sequential demand replenishment and facilitates an efficient performance evaluation of possible network configurations. We first model the scenario as a three-stage stochastic optimisation problem. We then solve it using the allocation rule and present an illustration of our analysis and the optimal supply chain network configuration. Furthermore, we derive some insights as to how different problem characteristics affect the value and usage of AM. [ABSTRACT FROM AUTHOR]

This study aims to develop a sustainable freight transportation network considering capacitated cross-docks for minimising the overall supply chain costs, including carbon emission cost. The problem is inspired by a major retail company based in India, which would like to expand its product portfolio in the new region. A mathematical model is developed to minimise total costs encompassing transportation cost, pipeline and retailers inventory cost, fixed cost of cross-dock and carbon emission costs. The deterministic time dependant demand, multiple products and multiple sourcing and distribution are some of the challenges faced by the retail industry. A two-level self-adaptive variable neighbourhood search algorithm is applied to solve a computationally complex problem. The results based on a two-level self-adaptive variable neighbourhood search algorithm are compared with the variable neighbourhood search algorithm to test the robustness of the developed model. Results reveal that an increase in retailers over suppliers significantly influences the number of open cross-docks. A multiple-case scenario approach captures the implications of varying capacity on the number of open cross-docks; thus, supporting the freight distribution managers in making sustainability-driven decisions. [ABSTRACT FROM AUTHOR]

Coiba National Park is an offshore region on the Pacific side of Panama, which hosts several endemic species of animals and plants. It was declared a UNESCO World Heritage Site in 2005. Despite the title awarded to the Park, knowledge about basic elements of its biodiversity are still lacking, which are of vital relevance for management and conservation policies. For instance, until now, no study had ever monitored the araneofauna diversity of the Park.Here, we provide the first checklist of spider species in Coiba National Park, including the main island and several surrounding islands. We sampled during several field trips carried out from August 2021 to August 2023. We identified at least 152 species (98 genera and 30 families) and we report three new spiders species for Panama, namely Ctenus nigrolineatus Berland (1913), Chapoda gitae Zhang & Maddison (2012) and Sarinda nigra Peckham & Peckham (1892). We discuss the implications of our results and recommend future lines of work that include DNA barcoding, monitoring of population and community dynamics, plus linkage of climatic data from the newly-installed meteorological station on the Island.

Inventorying and assessing geoheritage is a prerequisite for developing measures to preserve unique geological and geomorphological sites. Several researchers have developed methods for assessing and determining the value of geological and geomorphological sites. Given rapid environmental and climatic changes, it is crucial to improve the state of geoheritage assessment and inventory development. This overview presents an analysis of research on geoheritage assessment conducted in Morocco over the past 14 years (2008–2022). The objective is to provide an overview of the main methodological approaches. The analysis is based on a search of the Science Direct, Scopus, and Google Scholar databases to identify publications dealing mainly with Moroccan geoheritage sites. We find that most studies have concentrated on the identification and characterization of various geoheritage sites across the country, employing only the descriptive method. However, as the field has progressed, earth scientists are applying quantitative inventory and assessment methods, with some initiatives to propose new methods adapted to the Moroccan context.

The web-based office supplies requisition application is a significant step in modernizing office equipment procurement in various organizations, including universities. However, this website encounters problems due to immature planning and less effective implementation. The current website faces some problems with requesting office supplies on campus, where the current process lacks efficiency and transparency in the status of user requests. It often results in discrepancies between the registered stock of office supplies and the actual stock in the warehouse. Our research aims to improve this website using the Rapid Application Development methodology. We also include user feedback when designing this website. The result is a new web-based application that provides a much better user experience when requesting office supplies. This update is expected to increase the efficiency of office equipment request services, provide users with more transparent request status information, and ensure accurate stock availability.