Often, companies deliberately fulfill demands with delay since they can benefit from reducing transportation and setup costs. This paper aims at designing a four-echelon supply chain structure including multiple suppliers, multiple producers, multiple distributors and multiple customers. The objectives are to minimize the total operating costs of all the supply chain elements and to maximize the reliability of the system. A number of transportation systems with different reliability rates are considered. The paper mathematically formulates the problem as a mixed integer linear programming model. In order to solve the large-sized instances of the problem, the paper proposes a novel heuristic algorithm called Comparative Particle Swarm Optimization. This algorithm employs a mechanism in order to compare the generated solutions and to prevent from generating worse solutions. The results of different numerical experiments endorse the effectiveness of the proposed heuristic
A four-echelon supply chain network design with shortage: Mathematical modeling and solution methods
2015-03-29
oai:zenodo.org:3817065
Journal of Manufacturing Systems 35 164-175
Article (Journal)
Electronic Resource
English
Production–distribution , Supply chain , Comparative Particle Swarm Optimization , Concessive variable neighborhood search , Reliability , Closed-loop supply chain network design , Competitive location , Contract design , Facility disruptions , Fuzzy logic , Genetic Algorithm , Heuristic algorithm , Location-allocation problem , Lost sales , Maximal covering location problem , Multi-echelon , NSGA-II , Quota allocation , SCOR , Social responsibility , Supplier selection , Supply chain management , Sustainable supply chain network design , Tabu search , Vendor Managed Inventory
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