فصلنامه مدیریت زنجیره تامین
پیاپی 30 (پاییز و زمستان 1389)

In this article, a model for reverse logistics is presented. This model will be helpful for companies for decision making about used goods. In this model, effective criteria have been defined at first. Next, weight of criteria has been and finally, proposed algorithm is applied for decision making about used goods. Presented model leads to economical feasibility, costs minimizing and improving logistics potential of organization.

It is broadly recognized by global companies that supply chain management is one of the major core competencies for an organization to compete in the marketplace. Organizational strategies are mainly concentrated on improvement of customer service levels as well as reduction of operational costs in order to maintain profit margins. Therefore supply chain performance has attracted researchers’ attention. A variety of soft computing techniques including fuzzy logic and genetic algorithms have been employed to improve effectiveness and efficiency in various aspects of supply chain management.Meanwhile, an increasing number of papers have been published to address related issues. The aim of this paper is to summarize the findings by a systematic review of existing research papers concerning the application of soft computing techniques to supply chain management. Some areas in supply chain management that have rarely been exposed in existing papers, such as customer relationship management and reverse logistics, are therefore suggested for future research.