Parallel algorithms for continuous multifacility competitive location problems

J. L. Redondo, J. Fernández, I. García, P. M. Ortigosa
2009 Journal of Global Optimization  
We consider a continuous location problem in which a firm wants to set up two or more new facilities in a competitive environment. Both the locations and the qualities of the new facilities are to be found so as to maximize the profit obtained by the firm. This hard-to-solve global optimization problem has been addressed in [38] using several heuristic approaches. Through a comprehensive computational study, it was shown that the evolutionary algorithm UEGO is the heuristic which provides the
more » ... st solutions. In this work, UEGO is parallelized in order to reduce the computational time of the sequential version, while preserving its capability at finding the optimal solutions. The parallelization follows a coarse-grain model, where each processing element executes the UEGO algorithm independently of the others during most of the time. Nevertheless, some genetic information can migrate from a processor to another occasionally, according to a migratory policy. Two migration processes, named Ring-Opt and Ring-Fusion2, have been adapted to cope the multiple facilities location problems, and a superlinear speedup has been obtained.
doi:10.1007/s10898-009-9455-6 fatcat:int5erv7i5ef5it7ovpx2v7e7i