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| Multi objective optimization of distributed flexible flow shop scheduling considering the total carbon emissions and total cost of trucks |
| 投稿时间：2024-11-05 修订日期：2024-12-13 |
| DOI： |
| Key Words:Production scheduling Distributed flexible flow workshop Total carbon emissions of trucks multi-objective particle swarm optimization |
| Fund Project:国家自然科学基金(52305550)。 |
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| 摘要点击次数: 4 |
| 全文下载次数: 0 |
| Abstract:The distribution process is an indispensable part of industrial production. Reasonable distribution arrangements in the distribution process can not only reduce the production costs of enterprises, but also reduce the total carbon emissions of trucks, and assist enterprises in completing the task of energy conservation and emission reduction. Many manufacturing companies achieve the goal of reducing factory production costs and industrial carbon emissions by building an integrated operation mode of production and distribution. Therefore, this article constructs a distributed flexible flow workshop scheduling and logistics collaborative optimization model, with total cost and total carbon emissions of trucks as optimization objectives. We used multi-objective particle swarm optimization based framework to improve the global leader selection strategy and maintenance plan for the global leader profile. In the simulation experiment, multiple sets of examples are generated based on real data from a certain household paper manufacturing enterprise to test the performance of the algorithm. The results showed that compared with other particle swarm optimization algorithm in 10 cases, the improved multi-objective particle swarm optimization reduced the average total cost by about 3.29% and the average total carbon emissions of trucks by about 11.1%. |
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