Under the concept of a global economy, enterprises are assigning design and production environments around the world in different areas. A serious issue of information exchange emerges as companies use traditional hardware and very distinct software appropriate to their field of expertise. To overcome the problem of low productivity due to the interruption of information, the concept of simultaneous engineering and concurrent design becomes very significant. In this article an agent-based ship design system is developed to support cooperation in distributed ship design environments. Above all, the conflicts that occur while sharing knowledge in the system must be resolved. One approach is to adopt a case-based conflict resolution strategy formulated to resolve current conflict on the basis of similar previously resolved cases in agent-based collaborative design system environments. To do this, conflict cases that occur in the initial ship design stage are extracted. On the basis of the extracted cases, a case base is constructed. In addition, a conflict resolution handler located in the superagent called a facilitator, an agent to control other subagents, is developed to treat conflict problems effectively by case-based reasoning. The case-based conflict resolution strategy is evaluated by applying it to a collaborative design process in the initial ship design stage, especially the machinery outfitting design, the preliminary design, the hullform design, and the structural design. Through the help of the collaboration of the design agents, the facilitator, the conflict resolution handler, and the case-based system, a designer can make decisions based on similar previously resolved cases.

To obtain optimal design efficiently in the initial design stage of a ship, a hybrid system is developed by integrating the optimization algorithm and knowledge-based system. The hybrid system can manipulate numeric and symbolic data simultaneously. To increase search efficiency in a design space, the optimization algorithm (optimizer) is implemented by coupling a genetic algorithm (GA) and search method. The optimizer determines a candidate region around the optimum point by using the GA, then searches the optimum point by the search method concentrating in this region, thus reducing calculation time and increasing search efficiency. To generate input data for the optimizer, a rule-based system is developed. Some domain knowledge for ship optimization in the initial design stage is retrieved from a database of existing ship and design experts. The obtained knowledge is stored in the knowledge base. The optimizer incorporates a knowledge-based system with heuristic and analytic knowledge, thereby narrowing the feasible space of the design variables. Therefore, search speed and the capability of finding an optimum point will be increased in comparison with conventional approach. The developed system is applied principally to particulars of optimization of ships with multicriteria. Through application ship design, it shows that the hybrid system can be a useful tool for optimum design.