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Variable neighbourhood search heuristics for the probabilistic multi-source Weber problem / Altinel, I. K. in Journal of the operational research society (JORS), Vol. 62 N° 10 (Octobre 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 10 (Octobre 2011) . - pp. 1813–1826 Titre : Variable neighbourhood search heuristics for the probabilistic multi-source Weber problem Type de document : texte imprimé Auteurs : Altinel, I. K., Auteur ; N. Aras, Auteur ; Özkisacik, K. C., Auteur Année de publication : 2011 Article en page(s) : pp. 1813–1826 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Facility  location-allocation  Variable  neighbourhood  search  Probabilistic  Weber  problem  Heuristics Index. décimale : 001.424 Résumé : The Multi-source Weber Problem (MWP) is concerned with locating m facilities in the Euclidean plane, and allocating these facilities to n customers at minimum total cost. The deterministic version of the problem, which assumes that customer locations and demands are known with certainty, is a non-convex optimization problem and difficult to solve. In this work, we focus on a probabilistic extension and consider the situation where customer locations are randomly distributed according to a bivariate distribution. We first present a mathematical programming formulation for the probabilistic MWP called the PMWP. For its solution, we propose two heuristics based on variable neighbourhood search (VNS). Computational results obtained on a number of test instances show that the VNS heuristics improve the performance of a probabilistic alternate location-allocation heuristic referred to as PALA. In its original form, the applicability of the new heuristics depends on the existence of a closed-form expression for the expected distances between facilities and customers. Unfortunately, such an expression exists only for a few distance function and probability distribution combinations. We therefore use two approximation methods for the expected distances, which make the VNS heuristics applicable for any distance function and bivariate distribution of customer locations. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n10/abs/jors2010159a.html [article] Variable neighbourhood search heuristics for the probabilistic multi-source Weber problem [texte imprimé] / Altinel, I. K., Auteur ; N. Aras, Auteur ; Özkisacik, K. C., Auteur . - 2011 . - pp. 1813–1826. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 10 (Octobre 2011) . - pp. 1813–1826 Mots-clés : Facility  location-allocation  Variable  neighbourhood  search  Probabilistic  Weber  problem  Heuristics Index. décimale : 001.424 Résumé : The Multi-source Weber Problem (MWP) is concerned with locating m facilities in the Euclidean plane, and allocating these facilities to n customers at minimum total cost. The deterministic version of the problem, which assumes that customer locations and demands are known with certainty, is a non-convex optimization problem and difficult to solve. In this work, we focus on a probabilistic extension and consider the situation where customer locations are randomly distributed according to a bivariate distribution. We first present a mathematical programming formulation for the probabilistic MWP called the PMWP. For its solution, we propose two heuristics based on variable neighbourhood search (VNS). Computational results obtained on a number of test instances show that the VNS heuristics improve the performance of a probabilistic alternate location-allocation heuristic referred to as PALA. In its original form, the applicability of the new heuristics depends on the existence of a closed-form expression for the expected distances between facilities and customers. Unfortunately, such an expression exists only for a few distance function and probability distribution combinations. We therefore use two approximation methods for the expected distances, which make the VNS heuristics applicable for any distance function and bivariate distribution of customer locations. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n10/abs/jors2010159a.html