Alliance between agents and optimization in warehouse logistics

Nowadays, logistics has become an important part in the supply chain due to the effects of globalization. A warehouse is a large building where goods are stored, and where they may be shipped, catalogued, or received. When considering the level of effort involved in warehouse operations, the greatest expenditure of effort is in the picking process. In warehouse, the major goal is to improve the efficiency, accurancy and safety of warehouse operations. Supply chain managers focus to gain maximum efficiency for minimum cost. Therefore, Warehouse Management Systemd (WMS) first appeared on the market in the 1980s and have been developed to handle warehouse resources and track and monitor warehouse real-time operations. There are many application of Radio Frequency Identification (RFID) that can be found embedded in items especially in supply chain management. Verification is one of the crucial issues of RFID technology. The purpose of this study is to demonstrate the feasibility of a location using the RFID as an active technology in warehouse management field. In this content, our objective is to combine multi-agent systems and optimization algorithms in order to localize the operator by integrating the indoor positioning system and then optimize operator roote during the picking mission. In this paper, we present an Optimizer Based Agent Communication of Operator Work plan in Warehouse (OBACO2W). Order pickers, using the pick by voice technique, receive and execute the orders sent by the WMS. The purpose of logistics is to establish efficient and satisfy customers requirement. So, we aim to enhance workers productivity by assigning to the order pickers the shortest path for the picking mission. We must first locate the picker adopting the RFID technology. Multi-agent modeling problem can be divided into skills and knowledge to autonomous entities called agents, to provide links and dialogue between these entities by means of communication and interaction. In a multi-agent system, the change of status of certain objects in the environment of change agents can affect their behavior and decisions. Thus, to optimize their choices and to guide their taken decisions, these agents can be equipped with optimization approaches suited to their skills and knowledge. Hence the alliance between the multi-agent systems and optimization methods; these two approaches are perfectly complementary.