A new approach to cooperative competition in facility location problems: Mathematical formulations and an approximation algorithm
•This paper deals with cooperative competition in facility location problems.•A new game-theoretical multi-objective model is proposed that has efficient performance to achieve Nash equilibrium points.•Due to high computational complexity of the problem, a new approximation heuristic algorithm is pr...
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| Published in: | Computers & operations research Vol. 83; pp. 45 - 53 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
Elsevier Ltd
01.07.2017
Pergamon Press Inc |
| Subjects: | |
| ISSN: | 0305-0548, 1873-765X, 0305-0548 |
| Online Access: | Get full text |
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| Summary: | •This paper deals with cooperative competition in facility location problems.•A new game-theoretical multi-objective model is proposed that has efficient performance to achieve Nash equilibrium points.•Due to high computational complexity of the problem, a new approximation heuristic algorithm is proposed to solve large-sized problems.•The computational results show that the proposed algorithm has satisfactory performance in two criteria including computational time and the quality of final results.
This paper deals with cooperative competition in facility location problems in which potential players (investors) are in competition (or conflict) over acquiring suitable sites and clients. In order to formulate the problem, a game-theoretical multi-objective model with the objective of maximizing investor utility is presented. In the proposed method, an acceptance threshold constraint is applied to facility allocation that is based on a combination of distance between a facility and clients, and investors’ product prices. Since the common solution methods for multi-objective optimization, such as weighted sums, ε-constraints, multi-objective meta-heuristic algorithms, etc. are not efficient enough, and cannot guarantee achieving Nash equilibrium points, a new approach is developed to solve the presented problem. Moreover, according to the computational complexity of the problem, an approximation algorithm is introduced for large-sized problems. Finally, the computational results demonstrate that the proposed algorithm performs efficiently in obtaining Nash equilibrium points. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0305-0548 1873-765X 0305-0548 |
| DOI: | 10.1016/j.cor.2017.02.003 |