A Multi-objective Particle Swarm Optimization Based on Pareto Archive for Integrated Production and Distribution Planning in A Green Supply Chain
This paper presents a bi-objective model for integrated production and distribution planning in a multi-period multi-product green supply chain. This paper considers many near-real-world factors, such as: normal and overtime production shifts, limited storage capacity of the finished product and raw...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-01-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2020.1840197 |
| Summary: | This paper presents a bi-objective model for integrated production and distribution planning in a multi-period multi-product green supply chain. This paper considers many near-real-world factors, such as: normal and overtime production shifts, limited storage capacity of the finished product and raw materials, different vehicle types, direct and indirect shipping along with considering different production methods that influence the production costs and sale prices, simultaneously. Mixed integer programming model is proposed in which the profit maximization and the CO2 emission minimization are formulated. A particle swarm optimization algorithm based on Pareto archive that utilizes the genetic algorithm operators is proposed to solve the model. |
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| ISSN: | 0883-9514 1087-6545 |