Title :
Multiobjective Fitness Functions for Stable Marriage Problem using Genetic Algrithm
Author :
Ngo Anh Vien ; Chung, TaeChoong
Author_Institution :
Dept. of Comput. Eng., Kyung Hee Univ., Suwon
Abstract :
In this paper we propose a genetic algorithm (GA)-based approach to find out stable matchings in the stable marriage problem depending on different criteria such as stable matching with man-optimal, woman-optimal, egalitarian and sex-fair. The stable marriage problem is an extensively-studied combinatorial problem with many practical applications. Gale-Shapley (GS) algorithm is well known by which the stable matching found is extremal among many (for the worst case, in exponential order) stable matchings. So that Gale-Shapley algorithm can only search the man-optimal (or woman-pessimal) stable matching. The proposed algorithm has been evaluated by simulation experiment compared to other existing algorithms. It has been found that the proposed algorithm is quite efficient in finding stable matchings depending on different criteria
Keywords :
combinatorial mathematics; genetic algorithms; social sciences; stability; Gale-Shapley algorithm; combinatorial problem; egalitarian; genetic algorithm; man-optimal; multiobjective fitness functions; sex-fair; stable marriage problem; stable matchings; woman-optimal; woman-pessimal; Genetic algorithms; Genetic engineering; Samarium; Stable marriage; genetic algorithm; stable matching;
Conference_Titel :
SICE-ICASE, 2006. International Joint Conference
Conference_Location :
Busan
Print_ISBN :
89-950038-4-7
Electronic_ISBN :
89-950038-5-5
DOI :
10.1109/SICE.2006.315686