A population based hybrid meta-heuristic for the uncapacitated facility location problem

Authors:
Wayne Pullan
Affiliations:
Griffith University, Gold Coast, Australia
Venue:
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Year:
2009

Citing 4
Cited 0

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Abstract

The uncapacitated facility location problem is one of finding the minimum cost subset of m facilities, where each facility has an associated establishment cost, to satisfy the demands of n users where the cost of satisfying each user from all possible facilities is known. In this paper, PBS, a population based metaheuristic for the uncapacitated facility location problem is introduced. PBS uses a genetic algorithm based meta-heuristic, primarily based on cut and paste crossover and directed mutation operators, to generate new starting points for a local search. For larger uncapacitated facility location instances, PBS is able to effectively utilise a number of computer processors. It is shown empirically that PBS achieves state-of-the-art performance for a wide range of uncapacitated facility location benchmark instances.