Abstract
In this paper, we consider the competitive p-median facility location and design problem with elastic demand that we have earlier formulated based on the problem with elastic demand and the classical p-median problem. The situation that arises in a new company planning to enter the existing market of goods and services is considered. The firm wants to locate its businesses in p points, capturing as much of the profits from competitors as possible. The problem has a mathematical model with a non-linear objective function. Searching the optimal solution to the constructed problem is difficult. The CPU-time of commercial software is significant even for not too large dimension. For the new model, we have previously proposed variants of local search algorithms, and created a series of test instances based on real data. In this paper, an ant colony algorithm is developed, and an artificial ant algorithm is proposed. The algorithm’s parameters are adjusted taking into account the specifics of the problem. Experimental studies and comparison of the ant colony optimization algorithm with the simulated annealing are carried out.
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Acknowledgement
This research was supported by the Russian Foundation for Basic Research, grant 18-07-00599.
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Levanova, T., Gnusarev, A. (2019). Development of Ant Colony Optimization Algorithm for Competitive p-Median Facility Location Problem with Elastic Demand. In: Bykadorov, I., Strusevich, V., Tchemisova, T. (eds) Mathematical Optimization Theory and Operations Research. MOTOR 2019. Communications in Computer and Information Science, vol 1090. Springer, Cham. https://doi.org/10.1007/978-3-030-33394-2_6
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