Low-carbon Scheduling of Multi-objective Flexible Job-shop Based on Improved NSGA-II

被引：0

作者：

Jiang Y. ^{[1
]}

Ji W. ^{[1
,2
]}

He X. ^{[1
]}

Su X. ^{[1
]}

机构：

[1] School of Mechanical Engineering, Jiangnan University, Jiangsu, Wuxi

[2] Jiangsu Provincial Key Laboratory of Food Manufacturing Equipment, Jiangsu, Wuxi

来源：

Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2022年 / 33卷 / 21期

关键词：

flexible job-shop; low-carbon; multi-objective scheduling; non-dominated sorting genetic algorithm (NSGA-II);

D O I：

10.3969/j.issn.1004-132X.2022.21.006

中图分类号：

学科分类号：

摘要：

To solve the low-carbon scheduling problems of multi-objective flexible job-shops taking equipment energy consumption, tool wear and cutting fluid consumption as carbon emission sources and energy consumption and labor cost as processing cost, a low-carbon scheduling model was formulated to minimize carbon emission, makespan and processing cost, and an improved elitist NS-GA-II was proposed to solve the problem. Firstly, the chromosome composition was dynamically adjusted by encoding based on Tent chaotic map and greedy decoding based on analytic hierarchy process to improve the quality of the initial population. Then, an adaptive genetic strategy was proposed based on genetic parameters, which adjusted the crossover and mutation rates according to the population c-volution stage and the population non dominated state dynamically. Finally, based on external archives an improved elite retention strategy was designed to improve the population diversity in the later stages of the algorithm and retain high-quality individuals in the evolution processes. The effectiveness of the improved algorithm was verified by standard scheduling examples and a practical case. © 2022 China Mechanical Engineering Magazine Office. All rights reserved.

引用

页码：2564 / 2577

页数：13

共 31 条

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