运筹与管理 ›› 2019, Vol. 28 ›› Issue (2): 81-89.DOI: 10.12005/orms.2018.0036

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Seru生产方式下考虑工人异质性的多能工分配模型及算法

廉洁1, 刘晨光2, 殷勇3   

  1. 1. 西安理工大学 经济与管理学院,陕西 西安 710054;
    2. 西北工业大学 管理学院,陕西 西安 710072;
    3. 日本同志社大学 商学院,日本 京都 602-8580
  • 收稿日期:2017-03-27 出版日期:2019-02-25
  • 作者简介:廉洁(1987-),女,河北涞水人,讲师,研究方向:Seru生产;刘晨光(1974-),男,河南商丘人,教授,博士生导师,研究方向:管理决策理论与方法、可持续运营;殷勇(1970-),男,云南省人,教授,博士生导师,研究方向:Seru生产,产品模块化设计。
  • 基金资助:
    国家自然科学基金资助项目(71371153,71671139);中央高校基本科研业务费(3102018jcc010)

Mathematical Model and Algorithm for Multi-skilled Worker Assignment Problem in Seru Production Systems Considering the Worker Heterogeneity

LIAN Jie1, LIU Chen-guang2, YIN Yong3   

  1. 1. School of Economics and Management, Xi'an University of Technology, Xi'an 710054, China;
    2. School of Management, Northwestern Polytechnical University, Xi'an 710072, China;
    3. Business School, Doshisha University, Kyoto 602-8580, Japan
  • Received:2017-03-27 Online:2019-02-25

摘要: 多能工分配直接影响Seru生产系统的生产能力,而且为了适应Seru的频繁重组、实现生产能力的供需平衡,多能工应与生产任务一同分配。本文从提高工人间公平性和员工满意度的角度入手,研究了以实现Seru间和多能工间工作量均衡为目标的多能工分配问题。针对多能工的异质性特征,考虑了多能工技能组合与生产任务作业需求之间的匹配以及技能熟练水平对作业时间的影响。鉴于研究问题的NP-hard和多目标优化属性,基于第二代非支配排序遗传算法开发了模型求解算法。通过数值算例验证了模型和算法的有效性,分析了技能组合和技能熟练水平对Seru间和多能工间工作量均衡的影响。

关键词: 单元生产系统, 装配生产单元, 工作量均衡, 第二代非支配排序遗传算法

Abstract: Multi-skilled worker assignment determines productivity of seru production systems. In order to coordinate with frequent reconfigurations of serus and balance supply and demand for productivity, multi-skilled workers and production orders should be assigned to serus simultaneously. In view of the importance of interpersonal justice and worker satisfaction, a multi-skilled worker assignment problem with objectives of balancing inter-seru workload and inter-worker workload is solved in this paper. Owing to the heterogeneity of multi-skilled workers, more than one worker is available for a task and processing time of a task varies with proficiency level of the selected worker. An algorithm based on the non-dominated sorting genetic algorithm II is proposed to solve the mathematical model considering the NP-hard and multi-objective optimization nature of the problem. The proposed model and algorithm are tested by numerical examples and the impact of varying skill sets and proficiency levels on inter-seru and inter-worker workload balance is analyzed.

Key words: work-cell-based manufacturing systems, assembly cells, workload balance, non-dominated sorting genetic algorithm II

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