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In an unstable economic context, under the pressure of globalization and growing competition, many companies are seeing the limits of optimizing their distribution networks, and looking for new sources of competitiveness through optimizing their logistics networks and their relationships with their partners.
Every company in a local or international market is concerned with offering a product or service that is desired by the customer, relatively quickly, reasonably priced, and more efficient than that offered by the competition. In the near future, competition will not be between different companies, but between different supply chain networks.
Several activities are performed for the production of goods, such as raw materials procurement, production, distribution, and sales. Businesses rely on Decision Support Systems (DSSs) to manage these tasks.
Managing a business is primarily about exercising or delegating decision-making or management power. A decision is taken voluntarily by one or more decision-makers, leading to a choice between several possible solutions. This is crucial for the development of the company. Therefore, millions of decisions are made each day in companies at all levels and across all departments.
There is a large amount of scientific literature on supply chain coordination. This paper focuses on optimizing a distribution network, which consists of three levels: factories at the first level, distribution centers at the second level, and customers (points of sale) at the third level.
The problem addressed by this work is to determine a location at minimum cost for the corporate distribution center (warehouse) by minimizing the distances between distribution centers (warehouses) and customers (points of sale) and also minimizing the cost of grounds. It consists of finding the best location to build a new warehouse (site) among a set of candidate sites (possible location).
The objective of this process is to identify the best location for building a new warehouse (site) from a list of possible locations (candidates sites).
One of the most important tasks in the supply chain is designing distribution systems. The problem of locating distribution centers is always one of the biggest problems in the distribution process. Nowadays, distribution centers are essential to the distribution process.
The authors of this paper suggested a method to solve the localization problem using an optimization algorithm based on an artificial bee colony (Artificial Bee Colony algorithm) to build a new warehouse at a lower cost and well situated for clients (points of sale) for a more coordinated distribution network.
The artificial bee colony algorithm is a metaheuristic optimization method. Its principle is based on the behavior of the real bees in their life.
The ABC (Artificial Bee Colony) algorithm was developed by (Karaboga, 2005; Karaboga & Basturk, 2007), by observing the behavior of real bees to find food sources, which they refer to as nectar, and to share that information with the other bees in the nest through a dance behavior (Von Frisch, 1967).
The artificial bee colony algorithm have been developed for solving difficult optimization problem. Since it's invention, the ABC algorithm has been used to solve both numerical and no numerical optimization problems. The previous studies (Aghdam et al., 2009; Perez & Behdinan, 2007; Kao & Zahara, 2008; Zhang et al., 2009) have shown that algorithms based on swarm intelligent have a great potential and have attracted the attention of much researchers . in effect, the performance of ABC algorithm has been compared with some other intelligent algorithms, such as the Genetic Algorithm, and the Differential Evolution algorithm, and the results show that ABC algorithm is better than the other methods or at least comparable to them.
The working principle of the ABC algorithm adapted according to the problematic treated in this study is described later in the following sections.
The rest of the paper is organized as follows:
Section two presents a review of the previous literature on related work. Section three describes the issue addressed in this work, followed by the presentation of the contribution in section four. Results are presented in section five, followed by a comparative study in section six. Finally, the paper ends with a conclusion and some perspectives in the seven section.