A Population Based Hybrid Meta-heuristic for the Uncapacitated Facility Location Problem
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.
2009 World Summit on Genetic and Evolutionary Computation
© 2009 ACM. Self-archiving of the author-manuscript version is not yet supported by this publisher. For information about this conference please refer to the publisher's website or contact the author.
Information and Computing Sciences not elsewhere classified