Currently, there``s a cut throat competition in a retail industry and retail companies struggle for survival. Merchandise management - selecting desirable merchandises, disposing of slow-selling ones, ordering, and distributing them - is important to retailer``s success because merchandises are the basis of retailing. Until now, most retailers have depended on human beings for merchandise management. But because there are too many merchandises and brands, it is impossible for merchandise managers to evaluate, compare, select, and dispose of merchandises effectively. Retailers need a system which would accomplish merchandise managers`` jobs autonomously, continuously, efficiently, and efficiently. In this paper, we will propose an agent based system for merchandise management which performs evaluating & selecting merchandises and building purchase schedules autonomously in place of human merchandise managers. In order to facilitate agent``s intelligent behaviors, several tools such as DEA, EA, Linear Regression, Rule Induction Algorithm are incorporated into the system. And the proposed system is verified in its application to a duty-free shop.
The proposed system would accomplish merchandise management timely, autonomously, and efficiently and the effective merchandise management would reduce the inventory level while increasing raise sales and profits. The agent based merchandise management system will enhance a retail company``s competence for a success.