A hybrid metaheuristic algorithm to achieve sustainable production: involving employee characteristics in the job-shop matching problem

IF 4 Q2 ENGINEERING, INDUSTRIAL
Bingtao Quan, Sujian Li, Kuo-Jui Wu
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引用次数: 1

Abstract

ABSTRACT Sustainable production is proposed to guide manufacturers in achieving sustainable development goals. Although previous studies have developed diverse metaheuristics algorithms in finding the optimal method for balancing economic and environmental aspects, the social aspect is still omitted. In addressing this shortcoming, this study attempts to design a hybrid metaheuristic algorithm to balance economic performance with social expectations by matching the employees’ characteristics with those of a job shop. This study contributes to (1) confirming the importance of considering the social aspect for strengthening the theoretical basis; (2) proposing a hybrid metaheuristic algorithm in matching employees’ characteristics with the job shop; and (3) utilizing the optimal scenario leads the related firms in practicing sustainable production. The findings indicate that matching the employee-job-shop can fulfill the social expectation for generating positive effects on economic performance. If manufacturers insist on lowering labor costs, it may have a negative impact on production efficiency. Graphical Abstract
实现可持续生产的混合元启发式算法:将员工特征纳入作业车间匹配问题
可持续生产旨在指导制造商实现可持续发展目标。尽管先前的研究已经开发了多种元启发式算法来寻找平衡经济和环境方面的最佳方法,但社会方面仍然被省略。为了解决这一缺点,本研究试图设计一种混合元启发式算法,通过将员工的特征与就业商店的特征相匹配,来平衡经济绩效与社会期望。本研究有助于(1)确认考虑社会方面对于加强理论基础的重要性;(2) 提出了一种混合元启发式算法,用于将员工的特征与车间进行匹配;(3)利用最优情景引导相关企业实施可持续生产。研究结果表明,匹配员工工作场所可以满足对经济绩效产生积极影响的社会期望。如果制造商坚持降低劳动力成本,可能会对生产效率产生负面影响。图形摘要
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来源期刊
CiteScore
7.50
自引率
6.70%
发文量
21
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