Solving complex logistics problems with multi-artificial intelligent system

Abstract

The economy, which has become more information intensive, more global and more technologically dependent, is undergoing dramatic changes. The role of logistics is also becoming more and more important. In logistics, the objective of service providers is to fulfill all customers' demands while adapting to the dynamic changes of logistics networks so as to achieve a higher degree of customer satisfaction and therefore a higher return on investment. In order to provide high quality service, knowledge and information sharing among departments becomes a must in this fast changing market environment. In particular, artificial intelligence (AI) technologies have achieved significant attention for enhancing the agility of supply chain management, as well as logistics operations. In this research, a multi-artificial intelligence system, named Integrated Intelligent Logistics System (IILS) is proposed. The objective of IILS is to provide quality logistics solutions to achieve high levels of service performance in the logistics industry. The new feature of this agile intelligence system is characterized by the incorporation of intelligence modules through the capabilities of the case-based reasoning, multi-agent, fuzzy logic and artificial neural networks, achieving the optimization of the performance of organizations.