Application of a Capacitated Centered Clustering Problem for Design of Agri-food Supply Chain Network Fethi Boudahri 1 , Mohamed Bennekrouf 2 , Fayçal Belkaid 1 , and Zaki Sari 1 1 MELT Laboratory, University of Tlemcen, Algeria 2 EPST of Tlemcen, Algeria Abstract The supply chain of agricultural products has received a great deal of attention lately due to issues related to public health. Something that has become apparent is that in the near future the design and operation of agricultural supply chains will be subject to more stringent regulations and closer monitoring, in particular those for products destined for human consumption (agri-foods). This work is concerned with the planning of a real agri-food supply chain for chicken meat for the city of Tlemcen in Algéria. The agri-food supply chain network design is a critical planning problem for reducing the cost of the chain. More precisely the problem is to redesign the existing supply chain and to optimize the distribution planning. As mentioned in our paper, the entire problem is decomposed into two problems, and each problem is solved in sequential manner, to get the final solution. LINGO optimization solver (12.0) has been used to get the solution to the problem. Keywords: agri-food supply chains network, clustering cluster, optimization, CO2 emissions . 1. Introduction The The term agri-food supply chains (ASC) has been coined to describe the activities from production to distribution that bring agricultural or horticultural products from the farm to the table [1]. ASC are formed by the organizations responsible for production (farmers), distribution, processing, and marketing of agricultural products to the final consumers. The supply chain of agri- foods, as any other supply chain, is a network of organizations working together in different processes and activities in order to bring products and services to the market, with the purpose of satisfying customers’ demands [2]. These products must therefore be rapidly shipped from the sellers to the customers. More-over the demand of consumers on healthy products in ever increasing and the regulations of the authority require an improvement on current ASC planning. Still integrated approaches for ASC planning are limited, see [3]. Furthermore, literature on real design and distribution planning examples is rare. More precisely, the aim of this work is coordination of decisions for location, allocation and transportation of products to achieve an efficient and green logistic network design and distribution planning. Furthermore, environmental costs of road transportation in terms of CO2 emissions are taken into account in the computations. The Capacitated Centered Clustering Problem (CCCP) used in this study consists of defining a set of p groups with minimum dissimilarity on a network with n points. Demand values are associated with each point and each group has a demand capacity. The problem is well known to be NP-hard and has many practical applications. 2. State Of The Art The location problem is to determine the location of one or more sites, so as to optimize a mathematical function that depends on distances between these sites and a set of potential users. The study of location theory began formally in 1909 when Albert Weber considers a problem of locating a warehouse to minimize the total distance between the warehouses and customers. After Weber, Hakimi in 1960 had considered a more general problem that considers the location of one or more sites in a network in order to minimize the total distance between customers and these sites, or to minimize the maximum distance. [Florence Pirard 2005] gave the basic version of this problem as follows [11]: Minimize the sum of fixed costs of the locations and variable costs related to transportation. Constrained: Meet the entire demand from open sites. A .Problems allocation The allocation problem is to assign processing or manufacturing to the sites and determine the flow between the various network sites. This problem is expressed as follows [11]: Minimize the sum of costs of production and transportation. IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 1, July 2012 ISSN (Online): 1694-0814 www.IJCSI.org 300 Copyright (c) 2012 International Journal of Computer Science Issues. All Rights Reserved.