Logistics Management

In today's highly competitive global marketplace, the pressure on organizations to find new ways to create value and deliver it to their customers grows ever stronger. In the last two decades, the logistics function has moved to center stage. There has been a growing recognition that effective logistics management throughout the firm and supply chain can greatly assist in the goal of cost reduction and service enhancement. The keys to success in Logistics Management (LM) require heavy emphasis on integration of activities, cooperation, coordination and information sharing throughout the firm and the entire supply chain, from suppliers to customers. To be able to respond to the challenge of integration, modem businesses need sophisticated decision support systems based on powerful mathematical models and solution techniques, together with advances in information and communication technologies. Both industry and academia alike have become increasingly interested in using LM as a means of responding to the problems and issues posed by changes in the logistics function. This paper presents a brief discussion on the important issues in LM and argues that metaheuristics can play an important role in solving complex logistics problems derived from designing and managing logistics activities within the supply chain as a single entity. Among several possible metaheuristic approaches, we will focus particularly on Iterated Local Search, Tabu Search and Scatter Search as the methods with the greatest potential for solving LM related problems. We also briefly present some successful applications of these methods.