Abstract

Global competition and rapidly changing technologies are forcing major changes in the production styles and new manufacturing systems. Traditional centralized environments are not able to meet these requirements. In recent years, the internet has become the worldwide information platform for data and information sharing. Information processing is an important challenge in an internet-based environment. One of the new forms of manufacturing technologies based information techniques is supply chain management (SCM). The production-distribution planning problem (PDPP) is a suitable approach to support global optimization in SCM and should be solved within the integrated structure. This approach involves the determination of the best configuration regarding location, size, technology content and product range to achieve the firm's long-term goals. On the other hand, teams of autonomous agents Asynchronous teams (ATeams), co-operating by sharing solutions through a common memory, have been proposed as a means of solving combinatorial optimization problems. In this paper, a multi-agent framework is presented to solve production-distribution planning problem (PDPP) according to the client/server architecture in an internet-based environment, where three genetic algorithms (GAs) are assumed to be the agents of the model. This framework can help the system to select the most appropriate strategy and solution for competition and collaboration in an internet-based manufacturing system.

Key words: Internet-based environment, multi-agent system, client/server, production-distribution planning, supply chain, competition and collaboration.