Paper Info
Title
A memetic genetic algorithm for the vertex p-center problem
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.
Year
DOI
Venue
2008
10.1162/evco.2008.16.3.417
Evolutionary Computation
Keywords
Field
DocType
local search,satisfiability,genetic algorithm,combinatorial optimization
Memetic algorithm,Population,Artificial intelligence,Operator (computer programming),Genetic algorithm,Mathematical optimization,Crossover,Algorithm,Combinatorial optimization,Genetic representation,Local search (optimization),Mathematics,Machine learning
Journal
Volume
Issue
ISSN
16
3
1063-6560
Citations 
PageRank 
References 
1
0.37
17
Authors
1
Name
Order
Citations
PageRank
Wayne J. Pullan123212.73