A multi-agent system for selecting portfolio of new product development projects

Abstract

This paper is concerned with designing a multi-agent approach for evaluating new products and selecting product portfolio. In today’s companies it is widespread to execute many new product projects simultaneously. As these projects require resources that are available in the limited quantities, there is the need to select the most promising set of new product for development. The evaluation of new product projects involves many agents that analyse the customer requirements and information acquired from an enterprise system, including the fields of sales and marketing, research and development, and production. The company’s resources, performance metrics, and the identified relationships are stored in knowledge base that is specified according to the framework of constraint satisfaction problem. The relationships are sought with the use of fuzzy neural system and described in the form of if-then rules.