A multi-objective cellular genetic algorithm for energy-oriented balancing and sequencing problem of mixed-model assembly line

被引：47
|
作者：
Zhang, Beikun [1 ]
Xu, Liyun [1 ]
Zhang, Jian [1 ]
机构：
[1] Tongji Univ, Inst Adv Mfg Technol, Shanghai 201800, Peoples R China
来源：
JOURNAL OF CLEANER PRODUCTION | 2020年 / 244卷
基金：
中国国家自然科学基金;
关键词：
Energy saving; Mixed-model assembly line; Balancing; Sequencing; Cellular strategy; OPTIMIZATION METHOD; CARBON FOOTPRINT; CYCLE TIME; CONSUMPTION; MINIMIZE; CONSTRAINTS; TARDINESS;
D O I：
10.1016/j.jclepro.2019.118845
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Energy shortage has led to increasing concerns regarding energy-efficient manufacturing systems. In this study, an energy-oriented balancing and sequencing problem of mixed-model assembly line is proposed along with a cellular strategy-based genetic Algorithm. First, a bi-objective mathematical model with energy consumption and balance rate is developed. Second, a multi-objective algorithm that integrates a cellular strategy and local search is presented to solve this bi-objective problem. Third, a set of bench-mark problems is generated; the parameters of the algorithm are carefully set using the Taguchi method. The performance of the proposed algorithm is shown from two aspects: by a comparison with the algorithm without the cellular strategy and by a comparison with a non-dominated sorting genetic algorithm. Both the comparisons are conducted based on three given criteria. (C) 2019 Elsevier Ltd. All rights reserved.
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页数：16
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