Title :
Performance evaluation of genetic algorithms for flowshop scheduling problems
Author :
Murata, Tadahiko ; Ishibuchi, Hisao
Author_Institution :
Dept. of Ind. Eng., Osaka Prefecture Univ., Japan
Abstract :
The aim of this paper is to evaluate the performance of genetic algorithms for the flowshop scheduling problem with an objective of minimizing the makespan. First we examine various genetic operators for the scheduling problem. Next we compare genetic algorithms with other search algorithms such as local search, taboo search and simulated annealing. By computer simulations, it is shown that genetic algorithms are a bit inferior to the others. Finally, we show two hybrid genetic algorithms: genetic local search and genetic simulated annealing. Their high performance is demonstrated by computer simulations
Keywords :
digital simulation; genetic algorithms; optimisation; performance evaluation; scheduling; search problems; simulated annealing; simulation; computer simulations; flowshop scheduling problems; genetic algorithms; genetic local search; genetic operators; genetic simulated annealing; hybrid genetic algorithms; local search; minimizing; performance evaluation; scheduling problem; search algorithms; simulated annealing; taboo search; Computational modeling; Computer simulation; Genetic algorithms; Industrial engineering; Iterative methods; Job shop scheduling; Processor scheduling; Scheduling algorithm; Simulated annealing; Traveling salesman problems;
Conference_Titel :
Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1899-4
DOI :
10.1109/ICEC.1994.349951
