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A robust and efficient algorithm for planar competitive location problems
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AI
DOI：10.1007/s10479-007-0233-x.png)
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Abstract
En 中文
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 computatio 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.
Keywords:
Continuous location
Competition
Weiszfeld-like algorithm
Heuristic
Evolutionary algorithm
Computational study
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