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Tabu Search for the (r|p)-Centroid Problem Under Uncertainty Научная публикация

Конференция Optimization Problems of Complex Systems : International Asian School-Seminar
14-22 авг. 2023 , Новосибирск
Сборник 2023 19th International Asian School-Seminar on Optimization Problems of Complex Systems (OPCS)
Сборник, IEEE. 2023. 6 c. ISBN 9798350331134.
Вых. Данные Год: 2023, Страницы: 25-30 Страниц : 6 DOI: 10.1109/opcs59592.2023.10275754
Ключевые слова uncertain data, metaheuristic, centroid, bi-level programming
Авторы Davydov Ivan 1 , Kozhevnikov Roman 2
Организации
1 Mathematical models of decision making, Sobolev Institute of Mathematics, Novosibirsk, Russia
2 Mechanics and mathematics dept, Novosibirsk state university, Novosibirsk, Russia

Информация о финансировании (1)

1 Российский научный фонд 21-41-09017

Реферат: 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.
Библиографическая ссылка: Davydov I. , Kozhevnikov R.
Tabu Search for the (r|p)-Centroid Problem Under Uncertainty
В сборнике 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
Даты:
Опубликована в печати: 13 окт. 2023 г.
Опубликована online: 13 окт. 2023 г.
Идентификаторы БД:
Scopus: 2-s2.0-85175475020
OpenAlex: W4387620830
Цитирование в БД: Пока нет цитирований
Альметрики: