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The efficiency and responsiveness of supply chains are vitally dependent on inventory replenishment and transportation decisions. In this paper, we study a supply chain consisting of a single retailer ordering seasonal products within the newsvendor framework. The primary objective of the paper is to investigate the retailer's decision-making process, aimed at determining the optimal replenishment quantities and selecting the appropriate mix and size of the truck fleet. Initially, we formulate a mathematical model where the retailer exclusively manages a limited fleet of its own trucks for inbound transportation of a single seasonal product. In this context, we determine a lower breakeven point for the fixed transportation cost than what has been previously proposed in the literature. Subsequently, we examine a commonly encountered transportation scenario where the retailer has the opportunity to expand its fleet size by leasing trucks from the external market. The outcomes of the numerical example indicates that the flexibility resulting from the utilization of different types of trucks can lead to reduced overall costs. We also address the practical transportation problem of efficiently shipping various seasonal products solely with the retailer's own trucks. For this complex problem, we propose an optimal solution procedure based on Lagrangian method. We show that the joint replenishment of multiple products results in cost savings and enhances utilization of the trucks' capacities. [ABSTRACT FROM AUTHOR]

This paper adopts a holistic approach to the integrated water supply chain system, considering water-related aspects including production, technology selection, distribution routes, and storage, among others. It also introduces a multi-period comprehensive mathematical model that assists decision makers in jointly optimizing a multitude of decisions pertaining to the water supply chain, ranging from strategic to tactical ones. In particular, the former address the installation of new desalination plants along with their operational capacity, capacity expansion of existing plants and infrastructure assets (storage and distribution), as well as the selection of the best-suited desalination technologies. On the other hand, tactical decisions consider issues such as the allocation of water resources among end users, production level of desalinated water at the different plants, and storage levels across various demand zones. All these decisions are being optimized in every period towards minimizing financial and environmental costs throughout the planning horizon. To illustrate the model's practical relevance and assess its validity, a case study focused on an Emirate in the United Arab Emirates (UAE). Results highlight the need for increased desalination capacity over the next 15 years to match growing demand. The study pinpoints the timings for desalination facility expansions, compensating for decreased capacity due to degradation or retirement. The study underscores the superiority of reverse osmosis technology over other desalination options. [ABSTRACT FROM AUTHOR]

Supply-chain-based organisations are nowadays facing intense pressure to abide to environmental regulatory requirements while they are striving to be responsive to customers' needs at the least cost possible. As supply chain activities are among the top contributors to carbon emissions, several recent research works have investigated the impact of carbon regulation policies on economic and environmental supply chain performance. This paper presents integrated economic and environmental models for the one-vendor one-buyer supply chain problem under a vendor managed consignment inventory (VMCI) arrangement. Through the developed models, we study the impacts of two carbon reduction policies, namely carbon cap and carbon tax policies, on supply chain wide costs and carbon emissions. We first provide a much simpler and more compact formulation for the basic single-vendor single-buyer supply chain under VMCI agreement. We also present an environmental-based VMCI model where reduction of carbon footprint is considered as the only objective function. We then extend these two basic models to include each of the two carbon emissions reduction policies. We identify structural properties for the optimal solutions of the two hybrid economic and environmental models and propose algorithms to generate optimal solutions. The results of the computational experiments reveal that the implementation of carbon reduction policies, through carbon cap and carbon tax, may call for the adjustment of the vendor's production and buyer's delivery quantities to reduce carbon footprint without significantly increasing the operational costs. [ABSTRACT FROM AUTHOR]

This study considers a single vendor supplying a single retailer with a finished product packed in returnable transport items (RTIs), such as containers, pallets or crates, to facilitate its safe shipment. Once received at the retailer’s site, the RTIs are emptied, cleaned, repaired if needed and returned to the vendor to be used for the next shipment. Because of unexpected events, such as damage of RTIs and/or shortage of labour to empty RTIs, the RTI return time is considered stochastic in this study. In case the return of empty RTIs is delayed, the vendor has the option to rent RTIs from a nearby service provider to avoid disruptions in the delivery schedule and finished product shortages at the buyer’s premise. We formulate the problem of coordinating the flow of both the finished product and RTIs and minimising the supply chain wide costs as a mixed-integer non-linear programme. For a convex objective function, we develop an efficient solution procedure that generates the optimal replenishment cycle, the optimal number of RTIs and the optimal number of trucks. The general optimisation model and the solution procedure are illustrated for the case where the RTI return time is exponentially distributed. In addition, we conduct an experimental study to assess the impact of the problem parameters on the decision variables. It is found that renting RTIs is especially beneficial in case both shortage cost and the risk of late RTI returns are high. In addition, the average RTI return time is found to be critical for the performance of the supply chain. [ABSTRACT FROM PUBLISHER]

Abstract In response to the rising public concerns on environmental issues and the recently imposed governmental legislations and directives in this regard, companies nowadays ought to constantly adopt sustainable practices in their day-to-day operations. To that end, this paper seeks to optimize the replenishment strategy for a firm (e.g. retailer), who is facing a discrete time-varying demand for a temperature-sensitive (cold) product, while taking into account carbon emissions resulting from transportation and storage activities. In essence, the problem tackled herein is a variant of the classical dynamic lot-sizing problem (DLSP) for cold products with limited shelf life. To better resemble reality, we assume a stepwise cost function that is proportional to the number of fixed-capacity refrigerated trucks and cold stores used. We present three mathematical models, with the first being a cost minimization model, the second a carbon footprint minimization model, and the third a hybrid model that utilizes the carbon tax policy to jointly optimize both economic and environmental measures. We identify several structural properties of the optimal solution to the three models leading to the development of an exact solution algorithm based on the dynamic programming approach. The results of the computational experiments suggest that accounting for environmental aspects induces a change in the cost minimizing lot-sizing policy, resulting in a minor increase in the operational cost where the savings in the CO 2 related costs outweigh this minor increase. The two-way sensitivity analysis, conducted under randomized values of the demand, truck sizes, and cold stores capacities, indicates that higher savings in cost and carbon reductions are realized for increasing values of the carbon tax rate. Furthermore, on average, more cost savings and lower carbon emissions are also achieved when the values of the shelf life, truck size, and cold store capacity are increased. [ABSTRACT FROM AUTHOR]

Abstract: Resource leveling and time–cost tradeoff are among the most challenging optimization problems in project management. These two problems are usually addressed separately because each problem optimizes different objective functions. In this paper, we develop an integrated model that addresses both problems when activities are allowed to split for better utilization of resources. The formulated mixed integer linear program (MILP) model considers the tradeoff between the crashing‐dependent costs; direct and indirect costs, and resource utilization related costs; acquiring, releasing, and splitting costs. The model can be used as a decision tool to determine whether crashing is recommended when decision makers are also concerned with the better utilization of project's resources. A one‐way sensitivity analysis was conducted to assess total cost savings achieved through the integration of time–cost tradeoff and resource leveling problems. Another experimental study was undertaken to evaluate the performance of the MILP runtime. [ABSTRACT FROM AUTHOR]