A memetic genetic algorithm for the vertex p-center problem

Authors:
Wayne Pullan
Affiliations:
School of Information and Communication Technology, Griffith University, Gold Coast, QLD, Australia, w.pullan@griffith.edu.au
Venue:
Evolutionary Computation
Year:
2008

Citing 12
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Abstract

The p-center problem is one of choosing p facilities from a set of candidates to satisfy the demands of n clients in order to minimize the maximum cost between a client and the facility to which it is assigned. In this article, PBS, a population based meta-heuristic for the p-center problem, is described. PBS is a genetic algorithm based meta-heuristic that uses phenotype crossover and directed mutation operators to generate new starting points for a local search. For larger p-center instances, PBS is able to effectively utilize a number of computer processors. It is shown empirically that PBS has comparable performance to state-of-the-art exact and approximate algorithms for a range of p-center benchmark instances.