Using clustering method to solve Two Echelon Multi-products Location-Routing problem with Pickup and Delivery
Identifieur interne : 000C48 ( Main/Exploration ); précédent : 000C47; suivant : 000C49Using clustering method to solve Two Echelon Multi-products Location-Routing problem with Pickup and Delivery
Auteurs : Younes Rahmani [France] ; Ammar Oulamara ; Wahiba Ramdane Cherif- Khettaf [France]Source :
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Abstract
In this paper, we consider the Location Routing Problem in two-echelon network with Multi-Products, and Pickup and Delivery (LRP-MPPD-2E). The objective of LRP-MPP-2E is to minimize simultaneously the location and routing costs, considering many realistic non-tackled constraints in the literature. The first echelon deals with simultaneously selection of processing centers from a set of potential sites and the construction of the primary tours such that each primary tour starts from the main depot, visits the selected processing centers and returns to the main depot. The second echelon aims at assigning customers to the selected processing centers and defining the secondary tours. Each secondary tour, starts at a processing center, visits a set of customers, through one or several processing centers, and then returns to the first processing center. We develop a Hybrid Clustering Algorithm (HCA) with the objective of constructing Global-Clusters such that each Global-Cluster represents the set of clients associated to one feasible secondary tour, then Cplex Solver calculates the feasible tour within Global-Cluster. The HCA is compared with a Nearest Neighbour heuristic (NNH), which actually is the only available method for this problem, and with a Clustering-NNH in which Cplex solver is used to improve each secondary route obtained by NNH. An iterative version of HCA called IHCA is also implemented. Computational experiments are conducted to evaluate the performances of proposed approaches.
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The objective of LRP-MPP-2E is to minimize simultaneously the location and routing costs, considering many realistic non-tackled constraints in the literature. The first echelon deals with simultaneously selection of processing centers from a set of potential sites and the construction of the primary tours such that each primary tour starts from the main depot, visits the selected processing centers and returns to the main depot. The second echelon aims at assigning customers to the selected processing centers and defining the secondary tours. Each secondary tour, starts at a processing center, visits a set of customers, through one or several processing centers, and then returns to the first processing center. We develop a Hybrid Clustering Algorithm (HCA) with the objective of constructing Global-Clusters such that each Global-Cluster represents the set of clients associated to one feasible secondary tour, then Cplex Solver calculates the feasible tour within Global-Cluster. The HCA is compared with a Nearest Neighbour heuristic (NNH), which actually is the only available method for this problem, and with a Clustering-NNH in which Cplex solver is used to improve each secondary route obtained by NNH. An iterative version of HCA called IHCA is also implemented. Computational experiments are conducted to evaluate the performances of proposed approaches.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Metz</li><li>Nancy</li></settlement><orgName><li>Université de Lorraine</li></orgName></list><tree><noCountry><name sortKey="Oulamara, Ammar" sort="Oulamara, Ammar" uniqKey="Oulamara A" first="Ammar" last="Oulamara">Ammar Oulamara</name></noCountry><country name="France"><region name="Grand Est"><name sortKey="Rahmani, Younes" sort="Rahmani, Younes" uniqKey="Rahmani Y" first="Younes" last="Rahmani">Younes Rahmani</name></region><name sortKey="Ramdane Cherif Khettaf, Wahiba" sort="Ramdane Cherif Khettaf, Wahiba" uniqKey="Ramdane Cherif Khettaf W" first="Wahiba" last="Ramdane Cherif- Khettaf">Wahiba Ramdane Cherif- Khettaf</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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