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.
Highlights
In the economy, which has become more information intensive, more global and more technologically dependent, the role of logistics is becoming more and more important (Olavarrieta & Ellinger, 1997)
The principle of potential quality problem identification module (PQPIM) is that it adopts the Case-based reasoning (CBR) technology to identify the possible quality problems in the logistics workflow and divide them into several sub-problems based on different classes of the potential problems, which relies on the previous experience in similar cases
The third-party logistics company finds that the Intelligent Logistics System (IILS) helps identify all of the potential quality problems before providing service to customers in a faster manner compared with the traditional approach
Summary
In the economy, which has become more information intensive, more global and more technologically dependent, the role of logistics is becoming more and more important (Olavarrieta & Ellinger, 1997). The objective of service providers is to fulfill all customers’ demands while adapting to dynamic changes of logistics networks so as to achieve a high degree of customer satisfaction and a higher return on investment. As revealed from past research, post-purchase customer interactions and the customer's pre-purchase logistics service expectations can increase customer satisfaction, and the ability to provide a high level of logistics service. In order to facilitate the realization of providing high quality service, knowledge and information sharing among departments becomes a must in a fast changing market environment. The objective of this research is to develop the Integrated Intelligent Logistics System (IILS) in order to achieve high levels of service performance in the logistics industry.
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