A hybrid intelligent system to enhance logistics workflow: An OLAP-based GA approach

Abstract

In today's competitive environment, rapid advances in globalization and information technology have brought change at an unprecedented rate. Manufacturing, merchandising, and service companies are finding that their current approach for existing logistics operation no longer suffices. It is desirable to have a seamless and bi-directional interchange of information, coordination of decisions, and enhancement of assimilation of subsystems within and outside the relevant organization. In this paper, the proposed logistics workflow optimizer embraces the combination of On-Line Analytical Processing and Genetic Algorithm to provide decision support in different logistics activities within the supply chain. In addition, extensible Markup Language is incorporated to support the overall infrastructure, thereby providing essential support in enterprise integration. To validate the feasibility of the Internet-based logistics workflow optimizer, the implementation of the prototype in electronic industry is described, and the approach is applied to the business partner selection.

Keywords:

• OLAP
• XML
• Genetic algorithm
• Logistics workflow

Acknowledgements

The authors wish to thank the Research Committee of the Hong Kong Polytechnic University for the support of this project.