A Two-Level Parallel Genetic Algorithm for the Uncapacitated Warehouse Location Problem

A new genetic algorithm (GA) for the uncapacitated warehouse location problem (UWLP) and its parallelization are described. The parallel method is based on two ideas. (1) The GA is using a new integer coding for the UWLP. (2) The parallelization takes advantage of a developed two- level strategy. The first level of parallelization consists of executing several subpopulations of the GA concurrently with the occasional migration of individuals between them. On the second level, the solution space is separated into several disjunctive parts. The developed method, which is the first application of a parallel metaheuristic to the UWLP, is evaluated using a large set of 717 benchmark problems available from the literature, whereas the other known solution methods are always applied to subsets of these instances. The results show, that the parallel method is competitive with the best known solution methods so far.