Abstract
This paper is dedicated to the recent unprecedented boom of new supermarkets and hypermarkets in middle Europe. The motivation is to provide for the newcomers the tool for decision support, and to help answer the questions: "Is still economically advantageous to build new shopping malls and where to locate them?" We introduce the four versions of data correcting algorithm and three heuristics: simple exchange heuristic, exchange heuristics enhanced by simulated annealing metaheuristic, and genetic algorithm. All these methods were examined at the benchmarks of practical nature. This research showed the data correcting method as useable for practical instances of this problem. There were also identified interesting dependencies between the computational time and the number of competitors.
Highlights
In the area of middle Europe enormous boom of supermarkets and hypermarkets in the last years can be observed
We used the exchange heuristic (ExH) and simulated annealing (SA), which were used in the data correcting method
The described experiments have shown that the present exact solving methods are able to compute the Competitive Uncapacitated Location Problem to optimality in acceptable computational time for instances of problems, which correspond to reality
Summary
In the area of middle Europe enormous boom of supermarkets and hypermarkets in the last years can be observed. They quickly get a favour of customers and are very popular. The location of the store is considered as the most important because the neighbourhood of shopping center determines the level of competition, costs for supply management, labour costs, volume of demand, etc. In this paper we deal with the quantitative approach which allows performing a simple analysis of the supermarket chain extension. This approach can be used as a decision support tool for this difficult problem.
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