Multi-criteria human resources planning optimisation using genetic algorithms enhanced with MCDA

IF 0.7 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
M. Jurczak, Grzegorz Miebs, R. Bachorz
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引用次数: 0

Abstract

The main objective of this paper is to present an example of the IT system implementation with advanced mathematical optimisation for job scheduling. The proposed genetic procedure leads to the Pareto front, and the application of the multiple criteria decision aiding (MCDA) approach allows extraction of the final solution. Definition of the key performance indicator (KPI) reflecting relevant features of the solutions, and the efficiency of the genetic procedure provide the Pareto front comprising the representative set of feasible solutions. The application of chosen MCDA, namely elimination et choix traduisant la réalité (ELECTRE) method, allows for the elicitation of the decision maker (DM) preferences and subsequently leads to the final solution. This solution fulfils all of the DM expectations and constitutes the best trade-off between considered KPIs. The proposed method is an efficient combination of genetic optimisation and the MCDA method.
基于遗传算法的多准则人力资源规划优化
本文的主要目的是提供一个具有先进数学优化作业调度的IT系统实现示例。提出的遗传过程导致Pareto前沿,多准则决策辅助(MCDA)方法的应用允许提取最终解。关键绩效指标(KPI)的定义反映了解决方案的相关特征,以及遗传过程的效率,提供了包含可行解决方案代表集的帕累托前沿。所选择的MCDA的应用,即消除和选择交叉交叉法(ELECTRE),允许决策者(DM)偏好的启发,并随后导致最终的解决方案。此解决方案满足了DM的所有期望,并构成了所考虑的kpi之间的最佳权衡。该方法是遗传优化和MCDA方法的有效结合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Operations Research and Decisions
Operations Research and Decisions OPERATIONS RESEARCH & MANAGEMENT SCIENCE-
CiteScore
1.00
自引率
25.00%
发文量
16
审稿时长
15 weeks
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