Shop-floor scheduling at shipbuilding yards using the multiple intelligent agent system

The intelligent agent system has become a typical approach to research distributed artificial intelligence and distributed problem solving. However, despite its various technical advantages, the distribution and expansion of the intelligent agent system approach has been limited because existing methodologies rely on specialized applications and therefore require intensive investment to develop new systems. In an attempt to conquer these difficulties, a standardized methodology to construct intelligent agent systems is proposed. This approach deviates from current agent system approaches of repeatedly constructing new and customized expert systems. Specifically, it provides an economical method for developing intelligent agent systems by investigating the possibility of standardizing message communication protocols in linguistics speech-act theory and by supplementing traditional algorithmic systems with intelligent segments using, among others, expert system tools. To verify effectiveness, the shop-floor scheduling system of a large-scale shipbuilding yard has been redesigned, developed, and tested using this approach. This shop-floor scheduling system requires the scheduling of when and where to process block construction under various constraints. It is a difficult four-dimensional time and space allocation problem involving traditional NP-complete search spaces. The tested intelligent agent system proposes an innovative method for reducing the search space into three levels: the algorithm level, the agent intelligence level, and the level of cooperation among agents. It also provides methods for solving deadlock occurrence and non-uniformity problems resulting from parallel processing. Test results demonstrate applicability and economy, among other technical advantages.