Network performance of distributed coevolutionary agents

Innovations in software, networks, and database systems are enabling widely distributed organizations to integrate activities, share information, collaborate on decisions, and execute transactions. However, successful enterprise-wide collaboration is increasingly dependent on the availability of generalized decision-support tools that can efficiently access and utilize distributed information. This paper presents a basic theory and network-based performance evaluation of a class of coevolutionary algorithms that supports efficient planning in a distributed environment. Performance of these coevolutionary algorithms is evaluated in a distributed information architecture (coevolutionary virtual design environment) that supports integrated design-supplier-manufacturing planning. In this architecture, distributed evolutionary agents and mobile agents are principal entities that support a network-efficient exploration of planning alternatives in which successive populations systematically select superior planning alternatives.