One of the major planning problems faced by medium and large manufacturing enterprises is the distribution of production over various (production) facilities. The need for cross-facility capacity management is most evident in the high-tech industries having capital-intensive equipment and short technology life cycle. There have been solutions proposed in the literature that are based on the lagragian decomposition method which separate the overall multiple product problem into a number of single product problems. We believe that multi-agent systems, given their distributed problem solving approach can be used to solve this problem, in its entirety, more effectively. According to other researchers who have worked in this field, auction theoretic mechanisms are a good way to solve complex production planning problems. This research study develops a multi-agent system and negotiation protocol based on combinatorial auction framework to solve the given multi-facility planning problem.

The output of this research is a software library, which can be used as a multi-agent system model of the multi-product, multi-facility capacity allocation problem. The negotiation protocol for the agents is based on an iterative combinatorial auction framework which can be used for making allocation decisions in this environment in real-time. A simulator based on this library is created to validate the multi-agent model as well as the auction theoretic framework for different scenarios in the problem domain. The planning software library is created using open source standards so that it can be seamlessly integrated with scheduling library being developed as a part of the Advanced Planning and Scheduling (APS) system project or any other software suite which might require this functionality.

The research contribution of this study is in terms of a new multi-agent architecture for an Advanced Planning and Control (APS) system as well as a novel iterative combinatorial auction mechanism which can be used as an agent negotiation protocol within this architecture. The theoretical concepts introduced by this research are implemented in the MultiPlanner production planning tool which can be used for generating master production plans for manufacturing enterprises. The validation process carried out on both the iterative combinatorial framework and the agent-based production planning methodology demonstrate that the proposed solution strategies can be used for integrated decision making in the multi-product, multi-facility production planning domain. Also, the software tool developed as part of this research is a robust, platform independent tool which can be used by manufacturing enterprises to make relevant production planning decisions.