Application of Genetic Algorithm in Permutation Flow Shop to Optimize the Makespan

被引:0
作者
Pugazhenthi, R. [1 ]
Xavior, M. Anthony [1 ]
Shajahan, R. Mohamed [2 ]
机构
[1] VIT Univ, Sch Mech & Bldg Sci, Vellore 632014, Tamil Nadu, India
[2] Madha Engn Coll, Dept Mech Engn, Madras 600017, Tamil Nadu, India
来源
2014 IEEE INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND SYSTEMS (ICCCS'14) | 2014年
关键词
Genetic Algorithm; Flow shop; Exponential Distribution; Heuristic; Scheduling; SEQUENCING PROBLEM;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper addresses the modern manufacturing environment nature in the scheduling point of view. The scheduling is the vital criteria to allocate available resource over a period of time with one or more objective(s). The new heuristic (EPDT heuristic) is proposed for the flow shop problems to achieve the optimal makespan with the application of Genetic Algorithm (GA). This proposed heuristic approach, approximately solve the problem that consists in scheduling the jobs using Exponential Distribution factor which helps in developing a mathematical model with less computational instance. The characteristic of the heuristic was evaluated by solving Taillard benchmark problem in MATLAB environment. The EPDT heuristic yields a better result compared to classical heuristics; Palmer, CR, Gupta, and CDS heuristics.
引用
收藏
页码:160 / 163
页数:4
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