Experimental feedback on bioobjective permutation scheduling problems solved with a population heuristic

• Autorzy: Morita H. , Gandibleux X. , Katoh N.
• Języki publikacji: EN

Abstrakty

EN

Population heuristics present native abilities for solving optimization problems with multiple objectives. Using evolution and adaptation mechanisms, a population of individuals evolves in order to describe a good approximation of the efficient solutions. The resolution of the 1 | | (EC,- ,Tmaar) permutation scheduling problems, for which an exact algorithm is available, is investigated using a population heuristic based on genetic algorithms. The aim here is not to put in competition a heuristic method with an exact method but to give an experimental feedback on the resolution abilities of biobjective permutation scheduling problems with a population heuristic. The paper reports the aspects analyzed in this study : first, the pertinence of using genetic information into a population algorithm and second, a detailed multicriteria analysis of efficient solutions for this class of scheduling problems.

Słowa kluczowe

EN

multiple objective optimization; scheduling; population heuristic

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Foundations of Computing and Decision Sciences
• Rocznik: 2001
• Tom: Vol. 26, No. 1
• Strony: 23--50
• Opis fizyczny: Bibliogr. 41 poz.

Twórcy

autor

Morita H.

autor

Gandibleux X.

autor

Katoh N.

• Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 599-8231 - JAPAN,