An improved intelligent water drops algorithm for solving multi-objective job shop scheduling

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• 作者：S.H. Niu ; S.K. Ong ; A.Y.C. Nee
• 关键词：Multi-objective job shop scheduling ; Intelligent water drops ; Makespan optimization ; Tardiness optimization ; Mean flow time optimization
• 刊名：Engineering Applications of Artificial Intelligence
• 出版年：November, 2013
• 年：2013
• 卷：26
• 期：10
• 页码：2431-2442
• 全文大小：487 K

文摘

Multi-objective job shop scheduling (MOJSS) problems can be found in various application areas. The efficient solution of MOJSS problems has received continuous attention. In this research, a new meta-heuristic algorithm, namely the Intelligent Water Drops (IWD) algorithm is customized for solving the MOJSS problem. The optimization objective of MOJSS in this research is to find the best compromising solutions (Pareto non-dominance set) considering multiple criteria, namely makespan, tardiness and mean flow time of the schedules. MOJSS-IWD, which is a modified version of the original IWD algorithm, is proposed to solve the MOJSS problem. A scoring function which gives each schedule a score based on its multiple criteria values is embedded into the MOJSS-IWD鈥檚 local search process. Experimental evaluation shows that the customized IWD algorithm can identify the Pareto non-dominance schedules efficiently.