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Tabu Search for the (r|p)-Centroid Problem Under Uncertainty Full article

Conference Optimization Problems of Complex Systems : International Asian School-Seminar
14-22 Aug 2023 , Новосибирск
Source 2023 19th International Asian School-Seminar on Optimization Problems of Complex Systems (OPCS)
Compilation, IEEE. 2023. 6 c. ISBN 9798350331134.
Output data Year: 2023, Pages: 25-30 Pages count : 6 DOI: 10.1109/opcs59592.2023.10275754
Tags uncertain data, metaheuristic, centroid, bi-level programming
Authors Davydov Ivan 1 , Kozhevnikov Roman 2
Affiliations
1 Mathematical models of decision making, Sobolev Institute of Mathematics, Novosibirsk, Russia
2 Mechanics and mathematics dept, Novosibirsk state university, Novosibirsk, Russia

Funding (1)

1 Russian Science Foundation 21-41-09017

Abstract: We consider the (r|p)-centroid problem under an assumption of uncertainty in the input data. Two players, the leader and the follower, open facilities, striving to capture the largest market share. The leader opens p facilities, then the follower opens r facilities. Each customer chooses the nearest facility as his supplier and bring a particular income to the corresponding player. The aim is to choose p facilities of the leader in such a way as to maximize his market share. However, it is assumed that customers’ purchasing power is not known exactly and can change after the decision made. This problem can be represented as a bilevel programming problem. In this work, we propose a local search approach based on a stochastic tabu search framework to tackle the problem. We provide the results of numerical experiments and compare the behavior of both players compared to the deterministic setting of the same problem.
Cite: Davydov I. , Kozhevnikov R.
Tabu Search for the (r|p)-Centroid Problem Under Uncertainty
In compilation 2023 19th International Asian School-Seminar on Optimization Problems of Complex Systems (OPCS). – IEEE., 2023. – C.25-30. – ISBN 9798350331134. DOI: 10.1109/opcs59592.2023.10275754 Scopus OpenAlex
Dates:
Published print: Oct 13, 2023
Published online: Oct 13, 2023
Identifiers:
Scopus: 2-s2.0-85175475020
OpenAlex: W4387620830
Citing: Пока нет цитирований
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