拖延
数学优化
作业车间调度
渡线
人口
分类
调度(生产过程)
多目标优化
解算器
备品备件
计算机科学
流水车间调度
进化算法
工程类
数学
地铁列车时刻表
运营管理
算法
人工智能
操作系统
人口学
社会学
作者
Lingling Lv,Weiming Shen
标识
DOI:10.1016/j.jmsy.2023.03.002
摘要
In the context of collaborative manufacturing, integrated optimization of spare parts production and inventory management is practically important. This paper investigates an integrated production and inventory scheduling (IPIS) problem based on condition-based maintenance. In respect to this problem, whereby inventory and direct supply decisions are made simultaneously to achieve a better reduction in total inventory holding costs, total tardiness and total makespan, a multi-objective IPIS model is developed. An improved non-dominated sorting genetic algorithm-II with local search (INSGA-II_LS) is proposed for the multi-objective IPIS model. In INSGA-II_LS, the encoding and population initialization suited for IPIS are designed. The detailed presentation of operators of crossover, mutation, and local search that designed for the proposed IPIS problem then follows. The mathematical programming solver CPLEX and three multi-objective evolutionary algorithms called SPEA2, PESA-II, MOEA/D are designed for comparisons against INSGA-II_LS. Experimental results show the superiority of the proposed INSGA-II_LS for the IPIS problem with respect to various multi-objective performance metrics, especially for large-scale instances.
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