Variable neighborhood search for the p-median |
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| Affiliation: | 1. Department of Applied Informatics, School of Information Sciences, University of Macedonia, 156 Egnatia Str., Thessaloniki 54636, Greece;2. Department of Business Administration, School of Business Administration, University of Macedonia, 156 Egnatia Str., Thessaloniki 54636, Greece;1. Faculty of Mathematics, University of Belgrade, Belgrade, Serbia;2. Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria;1. Steven G. Mihaylo College of Business and Economics, California State University-Fullerton, Fullerton, CA 92834, United States;2. Department of Mathematics and Computer Science, The Royal Military College of Canada, Kingston, ON, Canada;3. LAMIH Laboratory, University of Valenciennes and Hainaut-Cambrsis Universit de Valenciennes, Le Mont Houy 59313, France;4. Centre for Logistics & Heuristic Optimization, Kent Business School, University of Kent, Canterbury CT2 7PE, United Kingdom;1. University of ?ilina, Faculty of Management Science and Informatics, Univerzitná 8215/1, 01026 ?ilina, Slovakia;2. University of ?ilina, University Science Park, Univerzitná 8215/1, 01026 ?ilina, Slovakia |
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| Abstract: | Consider a set L of potential locations for p facilities and a set U of locations of given users. The p-median problem is to locate simultaneously the p facilities at locations of L in order to minimize the total transportation cost for satisfying the demand of the users, each supplied from its closest facility. This model is a basic one in location theory and can also be interpreted in terms of cluster analysis where locations of users are then replaced by points in a given space. We propose several new Variable Neighborhood Search heuristics for the p-median problem and compare them with Greedy plus Interchange, and two Tabu Search heuristics. |
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