Performance evaluation of acceptance probability functions for multi-objective SA

Authors:
Hiroyuki Kubotani;Kazuyuki Yoshimura
Affiliations:
Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma-shi, Nara 630-0101, Japan;NTT Communication Science Laboratories, NTT Corporation, 2-4 Hikaridai Seika-cho, Soraku-gun, Kyoto 619-0237, Japan
Venue:
Computers and Operations Research
Year:
2003

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Abstract

A probabilistic local search algorithm called simulated annealing (SA) is a useful approximate solution technique for multi-objective optimization problems. When we use SA to solve multi-objective optimization problems, we cannot use an acceptance probability function used for single objective optimization problems. Therefore, several types of acceptance probability functions for multi-objective SA have been previously proposed. In this paper, we introduce a parameterized acceptance probability function for multi-objective SA, which changes its type depending on the parameter, and investigate how the performance of the multiobjective SA depends on the type of acceptance probability function in two test problems.