Multi-objective optimization for a combined location-routing-inventory system considering carbon-capped differences
| Autor: | Shoufeng Ji, Jinhuan Tang, Rongjuan Luo, Minghe Sun |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization 021103 operations research Control and Optimization Location routing Heuristic (computer science) Total cost Computer science Applied Mathematics Strategy and Management 0211 other engineering and technologies Particle swarm optimization 02 engineering and technology Inventory system Multi-objective optimization Atomic and Molecular Physics and Optics 020901 industrial engineering & automation Supply chain network Business and International Management Electrical and Electronic Engineering Integer programming |
| Zdroj: | Journal of Industrial and Management Optimization. 18:1949 |
| ISSN: | 1553-166X 1547-5816 |
| DOI: | 10.3934/jimo.2021051 |
| Popis: | A combined location-routing-inventory system (CLRIS) in a three-echelon supply chain network is studied with environmental considerations. Specifically, a bi-objective mixed integer programming model is formulated for the CLRIS to deal with the trade-offs between the total cost and the carbon-capped difference (CCD). A multi-objective particle swarm optimization (MOPSO) heuristic solution procedure is developed and implemented to solve the bi-objective mixed integer programming problem. The bi-objective mixed integer programming model and the MOPSO heuristic procedure are applied to a real-life problem as an illustrative example. The approximate nondominated frontier formed by solutions not dominated by others can be used for the decision makers to make trade-offs between the total cost and the CCD. Sensitivity analyses are conducted, and the relationship among the carbon cap, CCD, the total cost and the carbon prices are examined, and relevant managerial insights are provided. Comparisons with other existing algorithms show that the MSPSO heuristic procedure has very good performance. |
| Databáze: | OpenAIRE |
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