An Application Study of Multi-Agent Systems in Multi-Criteria Ship Design Optimisation

The overall complexity of optimisation problems in ship design results in high computation time requirements. The high computation time requirements for objective function evaluations in a complex design optimisation problem can practically be reduced by either using parallel execution of the objective functions in state-of-the-art super computers or concurrent execution of the objective functions in a distributed environment. In this paper, the distribution of the function evaluations is chosen to improve the performance of the optimisation algorithm. In the proposed distributed decision support environment, the tool for each objective function evaluation is represented as an agent. Agents are the excellent metaphors for devising a distributed environment, because they are able to encapsulate intelligence and tasks modularly as well as taking into account other agents in the environment. However, agents are not the entities, which do all the things for a person without human intervention. The designer of an agent must take into account all the details of the intelligence that the agent requires during its lifecycle. Furthermore, agents need to communicate in an environment, where the naming and role features are solved in order to allow them to co-operate, co-ordinate and be controlled within a certain extent. Multi-agent systems research focuses on three aforementioned topics basically communication, control and collaboration or negotiation. In this paper, the focus is given more on the communication aspects of multi-agent systems, the collaboration and control of the system is addressed by the multi-objective algorithm and the optimisation agent respectively. The optimisation algorithm in the proposed environment is implemented as a multi-objective genetic algorithm because of its capabilities of finding diverse and near Pareto-optimal solutions. The optimisation algorithm is parallelized in the objective function evaluations part of the NSGA II (A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization) and realized by using a multi-agent systems software environment. Two optimisation studies are presented in the paper. In the first optimisation problem, a simple test function is used for the validation of the distributed optimisation algorithm. In the second problem, an internal hull subdivision optimisation problem from the damage stability point of view is implemented and the results and the efficiency of the distributed version are presented. Finally, as one of future directions, the incorporation of the designer’s preferences in the optimisation study is discussed.