Network-based distributed planning for design and manufacturing

Planning in distributed environments requires efficient allocation of resources and access to information. This paper presents a basic theory and analysis of a class of distributed coevolutionary algorithms that supports planning in a networked environment. These algorithms are evaluated in a distributed information architecture that facilitates coevolutionary optimization of a design-supplier-manufacturing planning problem. Simulation analysis examines the percentage convergence error and the percentage computational advantage comparing the distributed algorithm to a centralized approach. The algorithms are evaluated in a realistic network setting and analyzed using models of network delays and processing times.