In recent years, many industries in developed countries have integrated the important process of reverse logistics into their supply chain for different reasons, including growing environmental concerns. Given fish as perishable food, re-employing unused products and waste in each step of the chain constitute a major concern for the decision-makers. The present study is conducted to maximize responsiveness to customer demand and minimize the cost of the fish closed-loop supply chain (CLSC) by proposing a novel mathematical model. To solve this model, the epsilon-constraint method and Lp-metric were employed. Then, the solution methods were compared with each other based on the performance metrics and a statistical hypothesis. The superior method is ultimately determined using the TOPSIS method. The model application is tested on a case study of the trout CLSC in the north of Iran by performing a sensitivity analysis of demand. This analysis showed the promising results of using the proposed solution method and model.

https://www.ije.ir/article_126180_950f85747040487fd2b766b547c2279f.pdf

Developing a Bi-objective Mathematical Model to Design the Fish Closed-loop Supply Chain

An essential aspect of a closed-loop supply chain (CLSC) involves its optimization. In this context, systematizing the publications on optimization methods applied in CLSC constitutes this research's primary objective. In this sense, a comprehensive literature review was carried out on 354 papers published from January 2008 to October 2020 to find future directions involving CLSC optimization. It was found stochastic methods are the primary approach in the studies regarding CLSC optimization, being applied in 27.68% of the publications investigated, while hybrid methods appeared in 21.75%, and deterministic methods were used in 20.62%. It was verified that 49.71% of the publications were related exclusively to strategic decisions concerning organizational decision-making levels, 22.03% analyzed tactical decisions, and 13.56% studied operational aspects. Regarding the sustainability dimensions, it was found that only the economic dimension was investigated in 70.62% of the analyzed publications. The three dimensions (economic, environmental, and social) were investigated simultaneously in only 6.21% of the publications. As the main conclusion, a lack of research covering the whole spectrum of the CLSC environment was found, comprising the various levels of organization decisions and sustainability dimensions of the triple bottom line.

Application of optimization methods in the closed-loop supply chain: a literature review

Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda

This paper investigates the multi-period and multi-echelon spare parts supply optimization problem. The periodic review order-up-to-S inventory policy is considered to determine the supply timing and the spare parts consumption. The spare parts consumption in lead time of each customer is calculated by the process of spare parts supply. A dynamic optimization mathematical model is developed to find the optimal supply scheme in each period with the objective of minimum total costs. In the dynamic optimization model, the parameters are changed with time. An improved particle swarm optimization algorithm is proposed to solve this dynamic problem. In the proposed algorithm, a change detector and a change response strategy are used to handle the change of optimization environment. We also adopt a self-adaption neighborhood search strategy to improve the ability of exploration and exploitation of the algorithm. Numerical experiment shows that the proposed strategy can improve the performance of algorithm greatly, and the model and solution method in this paper can be applied to optimize the spare parts supply in various scenarios.

/pdf/improved-dynamic-pso-based-algorithm-for-critical-spare-cl1pfpybto.pdf

Improved Dynamic PSO-Based Algorithm for Critical Spare Parts Supply Optimization Under (T, S) Inventory Policy

Designing the supply chain network is one of the significant areas in e-commerce business management. This concept plays a crucial role in e-commerce systems. For example, location-inventory-pricing-routing of an e-commerce supply chain is considered a crucial issue in this field. This field established many severe challenges in the modern world, like maintaining the supply chain for returned items, preserving customers’ trust and satisfaction, and developing an applicable supply chain with cost considerations. The research proposes a multi-objective mixed integer nonlinear programming model to design a closed-loop supply chain network based on the e-commerce context. The proposed model incorporates two objectives that optimize the business’s total profits and the customers’ satisfaction. Then, numerous numerical examples are generated and solved using the epsilon constraint method in GAMS optimization software. The validation of the given model has been tested for the large problems via a hybrid two-level non-dominated sort genetic algorithm. Finally, some sensitivity analysis has been performed to provide some managerial insights.

/pdf/a-hybrid-nsga-ii-algorithm-for-the-closed-loop-supply-chain-1m8d03jht3.pdf

A hybrid NSGA-II algorithm for the closed-loop supply chain network design in e-commerce

In this paper, a closed-loop location-inventory problem for spare parts is presented. The proposed supply chain network includes two echelons, namely (1) distribution centers (DCs) and repairing centers (RCs) and (2) operational bases. Multiple spare parts are distributed among operational bases from distribution centers in the forward supply chain and failed spare parts from operational bases are sent back to the repairing centers to receive multi-modal repair services in the reverse supply chain. The problem is formulated as a mixed-integer nonlinear programming model for the location-allocation problem that tries to choose which DCs and RCs to be opened and to determine the repair service mode of each failed items with objective function minimizing the total cost. Furthermore, the validation of the model is tested by GAMS software for small-sized problem, and particle swarm optimization (PSO) is proposed to solve large-sized problems in a rescannable time. Finally, several sensitivity analyses are presented to evaluate the proposed model.

https://www.ije.ir/article_73127_a921bb48f8539d1859f0aa2f66364c05.pdf

G Ahmadi

Papers

Closed-loop Supply Chain Inventory-location Problem with Spare Parts in a Multi-Modal Repair Condition