DocumentCode :
2909078
Title :
A population based hybrid metaheuristic for the p-median problem
Author :
Pullan, Wayne
Author_Institution :
Sch. of Inf. & Commun. Technol., Griffith Univ., Gold Coast, QLD
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
75
Lastpage :
82
Abstract :
The p-median problem is one of choosing p facilities from a set of candidates to satisfy the demands of n clients such that the overall cost is minimised. In this paper, PBS, a population based hybrid search algorithm for the p-median problem is introduced. The PBS algorithm uses a genetic algorithm based meta-heuristic, primarily based on cut and paste crossover operators, to generate new starting points for a hybrid local search. For larger p-median instances, PBS is able to effectively utilise a number of computer processors. It is shown empirically that PBS is able to effectively solve p-median problems for a large range of the commonly used p-median benchmark instances.
Keywords :
facility location; search problems; hybrid metaheuristic; hybrid search algorithm; p-median problem; population based hybrid metaheuristic; Clustering algorithms; Costs; Genetic algorithms; Helium; High level synthesis; Hybrid power systems; Lagrangian functions; Linear programming; Robustness; Terminology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4630779
Filename :
4630779
Link To Document :
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