Abstract: The paper is devoted to the development of methods for solving the robust p-median problem. In the modern economy, the decision-making process must consider the changing conditions. One way to account for such changes is to build robust models. Their purpose is to determine how much the task parameters can change so that the solution remains acceptable. The classical p-median problem is well known: it is necessary to locate p production points and serve customers in them at the lowest cost. In the robust version of the p-median problem, the stability associated with consumer demand is optimized. We consider the so-called threshold robustness. A nonlinear integer programming model is written out, and its linearization is performed. Using well-known software for this problem requires a lot of CPU time and computer RAM, so we develop approximate methods. To solve this problem, a problem-oriented versions of the Tabu Search and Variable Neighborhood Search Algorithms are proposed. Based on the ideas from the well-known library ”Discrete location problems”, a series of test instances were created. The parameters of the algorithms were adjusted, a comparative analysis of the quality of the developments was carried out, and the results were discussed.

Cite: Levanova T.V. , Khmara I.S.
Development of Tabu Search and Variable Neighborhood Search Algorithms for the robust p-median problem
In compilation MOTOR 2024: сборник тезисов XXIII Международной конференции «Теория математической оптимизации и исследование операций», (Омск, 30 июня – 06 июля 2024 г.). – Издательство ОмГУ., 2024. – C.62-63. – ISBN 978-5-7779-2691-3.

Dates:

Submitted:	Jun 26, 2024
Accepted:	Jun 26, 2024
Published print:	Jun 26, 2024
Published online:	Jun 26, 2024

Identifiers: No identifiers

Citing: Пока нет цитирований