Abstract
In this paper we empirically analyze several algorithms for solving a Huff-like competitive location and design model for profit maximization in the plane. In particular, an exact interval branch-and-bound method and a multistart heuristic already proposed in the literature are compared with uego (Universal Evolutionary Global Optimizer), a recent evolutionary algorithm. Both the multistart heuristic and uego use a Weiszfeld-like algorithm as local search procedure. The computational study shows that uego is superior to the multistart heuristic, and that by properly fine-tuning its parameters it usually (in the computational study, always) find the global optimal solution, and this in much less time than the interval branch-and-bound method. Furthermore, uego can solve much larger problems than the interval method.
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Redondo, J.L., Fernández, J., García, I. et al. A robust and efficient algorithm for planar competitive location problems. Ann Oper Res 167, 87–105 (2009). https://doi.org/10.1007/s10479-007-0233-x
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DOI: https://doi.org/10.1007/s10479-007-0233-x