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The climate crisis poses a dual threat to the environment and human health, with older adults being particularly vulnerable. This study aims to establish a network of elderly care facilities designed to respond to climate-induced disasters—an essential element in creating resilient cities that address the challenges of elderly care within the context of the climate crisis. First, we formulate an equation grounded in expert opinions to estimate demand in each region based on factors such as the elderly population, average age, frailty, and proximity to healthcare service nodes. We then introduce an Integrated Coverage and Distance Facility Location problem (ICDFL), a novel approach tailored to address the unique needs of seniors during disasters while considering governmental budget constraints. The ICDFL, therefore, simultaneously pursues two key objectives: (i) maximizing coverage while respecting a maximum allowable coverage radius, and (ii) minimizing overall travel distance. The first objective ensures the resilience of elderly health, guiding healthcare policymakers, while the second considers transportation and service costs faced by government agencies. To address dual-objective optimization, we utilize the epsilon-constrained optimization technique, which enables precise management of both coverage and distance goals through an iterative problem-solving approach. We apply the proposed model to a real-world case study in southern Ontario, Canada, to validate its effectiveness. This is an important aspect of the study, as Canada's warming trend is happening twice as fast as the rest of the world and its elderly population is expanding at an alarming rate. The results of our model provide guidance to policy makers and healthcare planners in improving emergency preparedness, thus creating a sustainable community for our growing elderly population and improving the well-being of older people during climate-induced disasters. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of pricing, product greenness, and coordination in a dual channel supply chain under channel disruption. It is assumed that one type of green product is being sold through a dual supply system. Also the movement of customers between channels in cases that only one of the channels is disrupted is surveyed. The decisions and profits of the supply chain and the members in the centralized and decentralized decision structures are extracted. In order to coordinate the supply chain, a transshipment contract is proposed and its application and usefulness is examined through a series of numerical examples and sensitivity analyses. The results illustrate that the proposed contract is capable of coordinating the supply chain and also guaranteeing the members' profitability. • Coordination of pricing and product greenness in a dual channel supply chain is analyzed. • Possible scenarios for channel disruption in both channels are investigated. • Developed model considers customer movement between channels if disruption occurs. • A transshipment contract is proposed to coordinate pricing and greening decisions in both channels. • The proposed coordination model results in more green products. [ABSTRACT FROM AUTHOR]

This paper investigates a two-echelon supply chain coordination problem in presence of consumer social awareness (CSA) when SC contributes in a cause-related marketing campaign. The channel consists of a manufacturer and a retailer where the manufacturer contributes in a CM campaign by donating a sum per sold item to the CM campaign. Two scenarios are analysed: (1) In the first scenario, the donation size as a portion of retail price is the only decision variable and paid by the manufacturer (2) In the second scenario, in addition to the donation size, retail price is a decision variable. In the first scenario, a cost sharing contract is proposed to improve channel performance while in the second scenario a collaborative model is developed to coordinate decisions of channel members. The numerical investigations illustrate that the proposed collaborative model not only increases the channel/members profit, but also creates a more socially concerned SC with lower retail prices. Moreover, the developed model helps supply chain managers to more effectively contribute in a CM campaign by making decision correctly on donation size. [ABSTRACT FROM AUTHOR]

This paper investigates a two-echelon reverse supply chain (RSC) consisting of a single remanufacturer and a single collector. The collector by offering a reward persuades consumers to take back their used products. Only items that meet the minimum quality level are accepted to be refurbished. There are two sources of uncertainties in the investigated RSC: (1) uncertainty in quality of returned products, (2) uncertainty in remanufacturing capacity. Under these circumstances, the amount of offered reward to consumers is a key problem. To optimize the whole RSC, the collector should determine the reward amount by considering the possibility of idle/overload capacity of the remanufacturing process. In the investigated RSC, the quality of returned products follows a uniform distribution and remanufacturing capacity follows a normal distribution. A customized revenue sharing mechanism is developed to share the risk of uncertainties between two members, fairly. The results indicate that, when remanufacturing capacity is limited, the suggested revenue sharing contract is able to share risks between participants and creates a win-win situation. In addition the suggested scheme is able to achieve channel coordination. [ABSTRACT FROM AUTHOR]

Abstract Nowadays, coordination of relief items procurement in humanitarian logistics has become one of the main challenges of disaster management. In this paper, we utilize a quantity flexibility contract (QFC) to coordinate ordering activities in a three-echelon relief chain. This multi-echelon supply chain consists of a relief organization (i.e., NGO), one relief item supplier, and affected areas. In the proposed QFC, initially, the relief organization places an order before the disaster strikes and is committed to purchasing the initial quantity no less than a previously agreed amount. On the other hand, the supplier is committed to providing up to a certain amount above the initial order, if needed. Expected profit functions of relief chain members include transportation cost, inventory cost, the manufacturing cost of relief items, shortage cost, salvage value, and satisfaction level of affected areas. Our findings show that, under demand uncertainty, the proposed QFC not only prevents significant losses at relief organization but also enhances satisfaction level of the affected areas. Finally, the performance of the proposed coordination model is examined via various numerical experiments and managerial insights are extracted. [ABSTRACT FROM AUTHOR]

Due to the increasing number of end-of-life (EOL) products and their related environmental concerns, much attention has been paid to reverse logistics. In this paper, we consider a two-echelon reverse supply chain (RSC) with one manufacturer and one retailer who try to improve sustainable consumption by increasing customers’ willingness to return used products through offering a discount or a direct fee in exchange for bringing back EOL products. Afterward, the model is extended to consider a closed loop supply chain (CLSC). Quantity discounts and increasing fee contracts are proposed to coordinate supply chains. Then, government role in improving coordinated supply chains through donating different incentives (tax exemption and subsidy) to supply chain members are analyzed. Results show that total channel profit in the coordinated case is improved. Also, in the proposed models, each member has enough motives to participate in the plan. In addition, results demonstrate that government-sponsored incentives to the manufacturer are preferred to the retailer. [ABSTRACT FROM AUTHOR]

This paper investigates the green channel coordination issue within a two-stage supply chain (SC). The investigated SC sells a non-green traditional product and also plans for releasing a new substitutable green product beside the current traditional product. Demand for both products is a function of the retail price as well as products’ green quality and retailer’s sales efforts. Both retail price and sales effort level for the green product are decided by the retailer while the product green quality is the manufacturer’s decision variable. Three decision scenarios are modelled and compared: (1) decentralized scenario where each member decides independently based on own profit, (2) integrated scenario where there is a one decision maker in the system, and (3) collaborative scenario that aims to enhance the overall channel profit subject to Pareto improvement for each member. Closed-form expressions of optimal retail price, sales effort and green quality are derived for the first two scenarios, and a mathematical programming model is developed for the collaborative scenario. Our numerical investigations revealed that the proposed collaboration model is capable of enhancing the SC profit fairly close to the centralized model and also ensures higher profits for both channel members than the decentralized decision making. [ABSTRACT FROM AUTHOR]

In this paper, destructive effects of upstream aggregated stochastic lead times on the supply chain (SC) performance are analyzed. For this purpose, a three-echelon SC consisting of one producer, one distributor, and one retailer is modeled. Both the producer and distributor face stochastic lead times, which can be also aggregated to create a long unpredictable lead time. In order to scale down shortages at the retailer site, an incentive scheme is proposed to convince the upstream members to increase their reorder points. Applying the coordinated model considerably increases the total profit earned by the whole SC as well as all SC members. [ABSTRACT FROM AUTHOR]

Highlights: [•] Coordination of service level in a two-stage SC is studied. [•] Controlling lead time variability using reliable shipping equipment is explored. [•] Contribution is about using lever of LT variability control for coordinating SC. [•] Both retailer and supplier conditions for participation in the plan are extracted. [•] Lead time variability control improves the whole SC sales volume and profitability. [ABSTRACT FROM AUTHOR]

• Cooperation of a food trading company and a peri-urban located recycling plant • Proposing a contract in a real food supply chain in order to reduce waste amounts • Recycling food waste by renting peri-urban located recycling facilities • Developing a quantity flexibility contract with standard and expedited lead times Optimization techniques in reverse logistics and closed-loop supply chains (CLSC) may effectively address food waste problem in urban areas. Motivated by recent advances in collecting/recycling food wastes through recycling supply chains, this study contributes to optimizing such a recycling channel in urban areas. We examine if renting waste-recycling facilities by a food trading company located in urban areas, where production/recycling processes are prohibited, is able to mitigate the problem. This paper examines a three-tier CLSC, including a trading company located in urban areas, a production plant located in peri-urban zones, and a food-waste-collector, in which food-waste is collected from restaurants/chain-stores for recycling purposes. The trading company rents waste-recycling facilities from the production plant in the peri-urban zones to carry out the relevant processes. To coordinate the channel, a novel Quantity Flexibility (QF) contract is developed. Results, based on a real case study in the meat products supply chain, show that profitability of the supply chain is increased using the proposed QF contract significantly (e.g., 30 percent increase in the food-waste-collector's expected profit). The findings from our developed models can help food supply chain managers to find cost-effective solutions for cooperating with other supply chain members. Our results show a Pareto-improvement outcome. [ABSTRACT FROM AUTHOR]

While unused medicines, by proper planning, can help people who need them but do not have access to them, huge medicine wastes in many pharmaceutical supply chains (PSCs) lead to severe economic losses and environmental/social damages. This paper aims to investigate a novel collaborative model to mitigate the entry of medicine wastes into the environment in a two-echelon PSC with an upstream-member (pharma-supplier) and a downstream-member (pharma-retailer) under the triple-bottom-line of sustainability. In this regard, a donation program is introduced to enhance the social aspect of the channel, and a take-back strategy is also presented to preserve the environmental and economic aspects of the PSC. In the investigated PSC, the pharma-supplier determines medication donation quantity; subsequently, the pharma-retailer by the aim of alleviating the risk of shortages decides on medication order quantity. Regarding the demand uncertainty and medications' fixed shelf-life, the probability of facing huge volume of outdated medicine is high. This study introduces a take-back strategy to reduce the risk of large volumes of medicine waste that includes collecting surplus items to use as part of donation programs or alternatively selling them in the secondary market. A bi-level optimization scheme is developed to coordinate the channel. The numerical results show that using the proposed bi-level optimization collaborative scheme not only can enhance total channel profit but also persuade both members to decide based on integrated sustainable PSC goals. Furthermore, the proposed model provides some practical orientations for pharmaceutical managers to reduce pharmaceutical waste, enhance the health level of the society, as well as maintaining all aspects of PSC sustainability. • A combined medicine donation and reselling program is investigated. • A bi-level optimization model is applied on a pharmaceutical supply chain. • The proposed model mitigates the risk of facing medicine wastes. • Not only the profitability, but the channel's social responsibility is enhanced. • A Pareto-improving outcome is achieved where both supply chain members earn more. [ABSTRACT FROM AUTHOR]

Leftover/end of life (EOL) medications not only cause financial losses for the pharmacy but also lead to disposal costs and high governmental penalties for the pharmaceutical supplier. In this study, a two-echelon pharmaceutical supply chain (PSC), including a single pharmaceutical supplier (pharma-supplier) and a single pharmaceutical retailer (pharmacy) with one type of fixed shelf-life medicine, is analyzed. A reducing pharmaceutical wastes scheme is developed to decrease relevant costs of leftover/EOL medicines, avoid governmental penalties, and also ensure patient service level (PSL). In the proposed model, excess medications are collected from the pharmacy warehouse based on the realized demand at a specific time before the expiration date to be resold in the secondary/alternative market. The introduced model is investigated in decentralized and centralized model structures. A novel combination of buyback and shortage risk-sharing contract (B&SRS) is proposed to attain channel coordination, maximize the whole PSC profits, and motivate members to participate in the scheme. The numerical investigation demonstrates that the proposed B&SRS contract can coordinate the developed PSC, enhance the whole channel profit, and also guarantee both channel members' profitability. Besides, the investigated model helps pharmaceutical managers to decrease EOL/expired medicines related costs and ensure PSL by making decision properly on buyback quantity. [ABSTRACT FROM AUTHOR]

Distribution feeder reconfiguration (DFR) in distribution systems can enhance operating conditions by reducing losses and improving voltage indices. This paper introduces a dual-stage risk-based framework that concurrently tackles day-ahead reconfiguration and microgrid scheduling within the distribution network. To control the negative aspects of uncertainties, the proposed framework integrates energy storage systems (ESS/HSS) and demand response programs (DRPs) at the network level, enhancing adaptability. The initial stage of the proposed model employs the AC power flow model, utilizing loss and voltage deviation functions as objective benchmarks for network reconfiguration. The scheduling is meticulously executed per interval, deriving optimized structures under diverse scenarios with the aid of a case reduction technique (CRT) to streamline solutions. The ultimate solution employs the grey wolf optimization (GWO) algorithm and CPLEX solver in the first and second stages respectively. Outcomes from applying this approach to the adjusted 118-bus network manifest improved operational conditions and voltage quality through reconfiguration. Impressively, the integration of ESS/HSS and DRPs yields a substantial 22.34% reduction in total operating costs, a conclusion substantiated by the numerical findings. Furthermore, by leveraging the CRT, a remarkable 56.17% reduction in problem-solution time is achieved. [Display omitted] • Investigating the impact of losses and voltage deviations on network performance. • Introducing a two-stage risk-based framework to determine the optimal topology. • Finding solutions to the micro-grids planning problem with the distribution network reconfiguration. • Adopting a case reduction method to lessen time demand required for solving the day-ahead planning problem. • Investigating the effect of demand response programs on the voltage characteristics and losses of the system. [ABSTRACT FROM AUTHOR]

In this paper, a fuzzy, closed-loop supply chain (CLSC), with one manufacturer, one retailer and one collector, is investigated. The optimal decision problem is analyzed based on a fuzzy price and sales effort-dependent demand to evaluate how members decide wholesale price, collection rate, retail price, and sales effort under different decision-making structures. Six game theory models are established and optimal solutions are extracted and compared by applying game and fuzzy theories. According to the results, collaboration between a manufacturer and retailer is favorable for both customers and the chain as a whole; the most effective model for collecting used products is collaboration between the manufacturer and collector. Finally, a practical, new channel coordination scheme is explored to match the performance of a decentralized CLSC to that of a centralized CLSC. The results illustrate that the proposed contract can effectively coordinate decentralized CLSCs. It is also beneficial from both consumer and environmental perspectives. [ABSTRACT FROM AUTHOR]

The rapid growth of technology, environmental concerns, and disruptions caused by the COVID-19 pandemic have led researchers to pay more attention to an emerging concept called the fifth industrial revolution (I5.0). Despite the high importance of the I5.0, the literature shows that no study investigated the supply chain network design problem based on the I5.0 pillars. Hence, this research develops a multi-stage decision-making framework to configure a closed-loop supply chain based on I5.0 dimensions to cover this gap. In the first stage, the score of technologies that utilized in the supply chain is calculated using the analytic hierarchy process method. Afterwards, in the second stage, a mathematical model is proposed to configure the supply chain. Then, Furthermore, an efficient solution method, named the fuzzy lexicographic multi-choice Chebyshev goal programming method, is developed to obtain the optimal solution. In general, the main contributions of the current study can be divided into two major parts as follows: (i) the current study is the first research that incorporates the dimensions of the I5.0 into the supply chain network design problem, and (ii) this work develops a novel and efficient solution method. In this regard, the major problems and challenges that existed include the limitation of available resources in relation to Industry 5, especially in the field of the supply chain, as well as quantifying the elements of Industry 5.0 in the form of a mathematical programming model. [ABSTRACT FROM AUTHOR]

In this paper, simultaneous coordination of visit interval and service level in a two-echelon pharmaceutical supply chain (PSC) with stochastic demand is studied. In the investigated model, a single pharmaceutical supplier (pharma-supplier) visits a single pharma-retailer at constant intervals and subsequently delivers the order after a deterministic lead-time. The pharma-retailer employs a periodic review inventory system and decides on the PSC service level, which impacts on the pharma-supplier's profitability. On the other hand, the pharma-supplier has full authority over the visit interval which determines order delivery frequency and consequently impacts on the pharma-retailer's inventory costs. Firstly, both members' decisions under decentralized and centralized decision-making structures are investigated, and afterward collaboration models are proposed in two different scenarios: (1) economic collaborative decision-making and (2) social collaborative decision-making. Finally, a set of numerical examples is carried out to compare the performance of different decision-making structures. The results indicate that collaborative decision-making on visit interval and service level could be of great benefit, both socially and economically. [ABSTRACT FROM AUTHOR]

• A Responsive supply chain based on the Industry 5.0 dimensions is investigated. • A stochastic Best-Worst Method is developed. • The medical devices industry is selected as a case study. Recently, managers and researchers have introduced the concept of Industry 5.0 that tried to improve Industry 4.0 by adding some crucial principles such as sustainability, resiliency, and human-centricity. Due to the importance of this concept, the present work develops a decision-making framework to investigate a responsive SC considering the Industry 5.0 dimensions named responsive Supply Chain 5.0 for healthcare systems. To do this, at the outset, the main related indicators and strategies are identified according to the experts and literature. Then, a new version of the best-worst method named stochastic best-worst method is developed to compute the indicators' weights. Afterwards, by employing the Fuzzy Vlse Kriterijumsk Optimizacija Kompromisno Resenje method, the feasible alternatives are ranked. The outputs indicate that responsiveness, sustainability, resilience, and human-centricity respectively are the most important aspects. On the other side, the high service level, cost reduction, recovery, and safety are the most important criteria in their corresponding aspects. Moreover, the achieved results show that using advanced technologies and collaboration and information sharing are the best alternatives. Also, to show the capability and advantages of the proposed method, we compare this method with the traditional methods (e.g., the analytical hierarchy process and the traditional best-worst method). In terms of the theoretical implications, this work has introduced the responsive supply chain 5.0 and developed a novel method. On the other hand, in terms of the managerial implications, the present work can give a comprehensive perspective to healthcare managers for understanding the concept of Industry 5.0 in the SC problem to improve the responsiveness of their businesses. [ABSTRACT FROM AUTHOR]

Given the requirements of international businesses, this research addresses the supply chain network design problem in the real-world situation by considering four critical features: sustainability, resiliency, responsiveness, and globalization. For this purpose, a multi-objective mathematical model is proposed that minimizes the environmental impacts and the total costs and maximizes the social impacts while considering the resilience and responsiveness of the global supply chain. Then, the modified fuzzy robust stochastic method is employed to tackle the uncertainty. This study selects one of the most important medical devices during the pandemic (COVID-19) namely the blood bank refrigerator as a case study. Afterwards, the proposed multi-objective model is solved by developing a novel method named as augmented lexicographic weighted Tchebycheff method. Based on the obtained results, an increase in the responsiveness level of the supply chain can lead to increasing the sustainability dimensions, including job opportunities, safety, carbon emission, and economic aspects. Moreover, an increase in demands harms the economic, environmental, and responsiveness targets. The demand has a pivotal role in selecting resilience strategy, as well. • A supply chain network is designed considering sustainability, resiliency, responsiveness, and globalization. • A modified fuzzy robust stochastic optimization approach is proposed. • An augmented lexicographic weighted Tchebycheff method is developed. • The blood bank refrigerator is selected as a case study. [ABSTRACT FROM AUTHOR]

This paper proposes a novel two-period option contract integrated with supplier selection and inventory prepositioning. A two-stage scenario-based mixed possibilistic-stochastic programming model is developed to cope with various uncertainties. The first stage's decisions include supplier selection and capacity reservation level at each supplier/period and the level of inventory prepositioning. Furthermore, decisions regarding the time and exercised amount are made in the second stage. Applicability of the model is validated through a real case study. Finally, several sensitivity analyses are conducted to examine the effect of important parameters on the solutions to gain useful managerial insights. [ABSTRACT FROM AUTHOR]

Humanitarian organizations typically pre-position relief items in strategic locations whose optimum levels are affected by the amounts of pre-disaster contractual agreements and post-disaster procurements. To account for these interrelationships, this paper proposes a novel two-stage scenario-based mixed fuzzy-stochastic programming model for integrated relief pre-positioning and procurement planning based on a quantity flexibility (QF) contract under a mixture of uncertain data. An effective multi-step solution method is also devised to solve the problem in real-sized instances. Applicability of the proposed model is examined through a real case study. Finally, a number of sensitivity analyses are conducted to provide helpful managerial insights. [ABSTRACT FROM AUTHOR]

This study presents a multi-objective mathematical model for integrating upstream and midstream segments of crude oil supply chain in the context of environmental indicators. An actual case study in the Persian Gulf is considered. Upstream and midstream segments are integrated into the presented model due to their significant interaction. Also, oilfield development and transformation planning are considered simultaneously along with green aspects. The bi-objective optimization considers net present value (NPV) and environmental issues. A unique multi-objective evolutionary algorithm based on decomposition (MOEA-D) approach is employed to solve the proposed mixed integer nonlinear programming model. The results of MOEA-D are compared with the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO). The results indicate the superiority of the MOEA-D approach for large size problems. [ABSTRACT FROM AUTHOR]

In this study, we propose an imperfect economic production quantity model with both upstream and downstream trade credits. Trade credit is offered to the manufacturer by the supplier if the order quantity of raw material exceeds a predetermined value. Moreover, customers are permitted to pay the purchasing cost to the manufacturer after receiving the products . However, defective items are sometimes produced during the production process. Therefore, another assumption is made that defective items are produced during the production period and they all become perfect after a reworking process. In order to solve the model in several different cases, we show that all of the proposed costs functions are convex and optimal solutions are obtained mathematically for the production lot size and backlogged shortage. Furthermore, to discover the effects of a two-level trade credit period and the reworking of defective items, illustrative examples are provided as well as a sensitivity analysis to demonstrate the results of the model. [ABSTRACT FROM AUTHOR]

Development of strategies to control urban air pollution is a complex process involving a wide range of sciences. In this study a system dynamics model is proposed in order to estimate the behavior of parameters affecting air pollution in Tehran. The proposed model includes two subsystems: (1) urban transportation, (2) air polluting industries. In this paper, several policies are proposed to mitigate air pollution. The proposed model is simulated under several scenarios using historical data of transportation and industrial sectors in Tehran. Policies are categorized as: (1) road construction, (2) technology improvement in fuel and automotive industries, (3) traffic control plans, (4) development of public transportation infrastructures. The results show effectiveness of the proposed policies. In this case, technology improvement in fuel and automotive industries and development of public transportation infrastructures are more effective policies in order to reduce air pollution. [ABSTRACT FROM AUTHOR]