在一个集成的机械零件调度和车辆路由问题中的碳排放的优化及其使用MOPSO和NSGAII元启发算法的解决方案
Ali Heidari1, Amir-Hosein Sheikh-Azadi2, Atefeh Hasan-Zadeh3
1School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Scientific reports
|October 30, 2024
概括
这项研究引入了一种新模式,将生产和车辆路线整合起来,以最大限度地降低环境影响和成本. MOPSO算法有效地平衡了生产规划中的经济,环境和社会因素.
科学领域:
- 运营研究 运营研究
- 环境管理环境管理
- 工业工程 工业工程 工业工程
背景情况:
- 全球经济增长增加了能源消耗和温室气体排放,导致环境恶化.
- 当前的生产系统优先考虑经济因素,忽视节能和减少排放的战略.
- 将车辆路线与生产规划相结合,特别是车间运营前的路线,是一个新的挑战.
研究的目的:
- 开发一个双目标的数学模型,用于集成的生产和车辆路线,重点关注环境,社会和经济方面.
- 为弥补研究中关于路由先于车间生产的模型的差距.
- 优化生产规划以减少碳排放和提高客户满意度.
主要方法:
- 开发一个包含环境,社会和经济目标的混合整数线性编程 (MILP) 模型.
- 应用增强的epsilon-constraint (AEC) 方法来解决双目标模型.
- 使用MATLAB软件与MOPSO (多目标粒子群优化) 和NSGA-II (非主导排序遗传算法II) 进行复杂的高维问题.
主要成果:
- 与NSGA-II相比,MOPSO算法在七个评估标准中表现出优越的性能.
- 综合模型成功地在生产规划中平衡了经济,环境和社会目标.
- 在最小化污染和确保按时交付客户之间确定了一个权衡.
结论:
- 决策者必须仔细考虑环境保护和客户满意度之间的平衡.
- 尽量减少污染可能需要调整交付时间表,需要进行战略性权衡.
- 开发的模型和算法为可持续和高效的生产车辆路由系统提供了一个框架.
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