Random search with species conservation for multimodal functions

Abstract

This paper is to investigate the influence of a minimum population size on the performance of the species conservation technique in searching multiple solutions. The species conservation technique is combined a random search technique, which is a special genetic algorithm with one individual, to present an algorithm, called species conservation random search (SCRS), for solving multimodal problems. Each species is built around a dominating point, called the species seed, with a given species radius, and the species are saved in the species set. The random search is used to explore a new point in the neighborhood area of an initial point randomly selected from the species set. A modified species conservation technique has been developed to update species seeds according to these new exploration points. Numerical experiments demonstrate that the proposed SCRS is very effective in dealing with multimodal problems and can also find all the global solutions of test functions.

A Partition-Based Random Search Method for Multimodal Optimization

“…In restricted tournament selection [29], the new generated individuals compete with the nearest individuals in a subpopulation randomly sampled from the population. In species conservation [30,31], the species seeds dominating other individuals in the same species are conserved into the next generation and updated iteratively. Li [32] designed a ring topology [33] on the particle swarm and used the lbest PSO to create small niches without niching parameters.…”