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Dry port can speed the flow of cargo between ships and major land transportation networks while reducing carbon emissions and relieving seaport congestion. This study introduces a continuous approximation model to facilitate the design of a seaport-dry-port network that takes carbon emissions into account. Multimodal transport with two transport modes: rail and road are considered. Containers are delivered quickly from shippers to dry ports through road transport; then transferred to seaport through rail transport to save money and reduce carbon emission. For decision-making scheme, a game theory is used to help the seaport, dry ports, and shippers optimize their own benefits and guide them to determine their decision variables. A nonlinear optimization technique is used to solve this seaport-dry-port network design problem. The closed-form of all decision variables is found directly. A numerical study is conducted to derive managerial insights. The results show that the development of dry port concepts and multimodal transports could reduce the carbon cost from road transport.

This paper reports on a closed-loop supply chain network for the remanufacturing of products under RFID technology. RFID technology can be used in a closed-loop supply chain to improve the efficiency of ordering and the operation of a just-in-time remanufacturing system; however, this invariably incurs costs. Companies must carefully consider the opportunities and challenges posed by RFID technology to ensure that such an investment is worthwhile. This study contributes to the body of existing closed loop supply chain literature through formulating the problems as continuous functions to reduce the complexity of the problems and decrease the amount of data required which greatly facilitates development and implementation. The objective of this study was to determine the number of distribution centers, the number of remanufacturing centers, the joint replenishment cycle time, and the investment in RFID required to minimize total network costs. This paper applies a continuous approximation (CA) approach to model the network. Nonlinear programming techniques are developed to solve the optimization problems. The results of numerical analysis demonstrate that the adoption of RFID could be highly beneficial to companies. We also investigate the effects of parameter values on costs and decisions to gain managerial insight.

Growing awareness of environmental issues is prompting the development of sustainable supply chain management. Closed-loop supply chains in which used products can be returned for remanufacture are becoming increasingly popular. This paper introduces a two-phase approach to the design of supply chain networks taking into account carbon emission and remanufacturing. In the first phase, a continuous approximation model is used to design the forward supply chain network. The objective is to minimize the total forward network cost by simultaneously determining the number and the service areas of distribution centers (DCs) and the replenishment cycle time for DCs. A nonlinear optimization technique is used to solve the forward supply chain network design problem. In the second phase, a reverse supply chain network is formulated based on the results of the first phase to determine the optimal number and service areas of remanufacturing centers (RCs) and the replenishment cycle time for RCs. Finally, numerical analyses are conducted to show the solution approach and provide some managerial insights.

Deteriorating items, trade credit, and partial backordering are common in today’s business. However, no previous study on supply chain network design has considered these business aspects together. In this paper, we present supply chain networks designed for deteriorating items under trade credit and two conditions: (a) no shortage and (b) partial backordering of goods. We also present 2 algorithms based on nonlinear optimization that were developed in order to optimize the influence area and the joint replenishment-cycle time in the no-shortage case, and to identify the optimal shortage level in the partial-backordering case. The numerical examples presented herein illustrate how the solution procedure works. The effects of various values of the tested parameters on decisions and costs are also discussed. Our results could be used as a reference by managers when making business decisions.