作者
Willian Tessaro Lunardi, Holger Voos
发表日期
2018
研讨会论文
33rd ACM/SIGAPP Symposium On Applied Computing, Pau, France, April 9-13, 2018
简介
Flexible job-shop scheduling problem (FJSP) is one of the most challenging combinatorial optimization problems. FJSP is an extension of the classical job shop scheduling problem where an operation can be processed by several different machines. The FJSP contains two sub-problems, namely machine assignment problem and operation sequencing problem. In this paper, we propose and compare a discrete firefly algorithm (FA) and a genetic algorithm (GA) for the multi-objective FJSP. Three minimization objectives are considered, the maximum completion time, workload of the critical machine and total workload of all machines. Five well-known instances of FJSP have been used to evaluate the performance of the proposed algorithms. Comparisons among our methods and state-of-the-art algorithms are also provided. The experimental results demonstrate that the FA and GA have achieved improvements in …
引用总数
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