Restart Scheduling for Genetic Algorithms

Abstract. In order to escape from local optima, it is standard practice to periodically restart a genetic algorithm according to some restart criteria/policy. This paper addresses the issue of finding a good restart strategy in the context of resource-bounded optimization scenarios, in which the goal is to generate the best possible solution given a fixed amount of time. We propose the use of a restart scheduling strategy which generates a static restart strategies with optimal expected utility, based on a database of past performance of the algorithm on a class of problem instances. We show that the performance of static restart schedules generated by the approach can be competitive to that of a commonly used dynamic restart strategy based on detection of lack of progress.

• Type: Conference
• Year: 1998
• Where: PPSN
• Authors: Alex S. Fukunaga
• Keywords: Distributed And Parallel Computing, PPSN 1998, Restart Criteria/policy, Restart Strategy, Static Restart