Title :
Multi-objective genetic local search algorithm
Author :
Ishibuchi, Hisao ; Murata, Tadahiko
Author_Institution :
Dept. of Ind. Eng., Osaka Prefecture Univ., Japan
Abstract :
Proposes a hybrid algorithm for finding a set of non-dominated solutions of a multi-objective optimization problem. In the proposed algorithm, a local search procedure is applied to each solution (i.e. to each individual) generated by genetic operations. The aim of the proposed algorithm is not to determine a single final solution but to try to find all the non-dominated solutions of a multi-objective optimization problem. The choice of the final solution is left to the decision maker´s preference. The high searching ability of the proposed algorithm is demonstrated by computer simulations on flowshop scheduling problems
Keywords :
digital simulation; genetic algorithms; manufacturing data processing; production control; scheduling; search problems; computer simulations; decision maker preference; flowshop scheduling problems; genetic operations; hybrid algorithm; multiobjective genetic local search algorithm; multiobjective optimization problem; nondominated solutions; searching ability; Computer simulation; Genetic algorithms; Industrial engineering; Job shop scheduling; Processor scheduling; Scheduling algorithm; Simulated annealing;
Conference_Titel :
Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
Conference_Location :
Nagoya
Print_ISBN :
0-7803-2902-3
DOI :
10.1109/ICEC.1996.542345
