Dynamic multiobjective optimization for thrust allocation in ship application

Abstract Thrust allocation is a key procedure in the dynamic position system (DPS) of marine vessels. The present work aims to study the characteristics of dynamic optimization in thrust allocation. A two-phase analysis process is proposed. In phase-I, the model for thrust allocation is generated from the viewpoint of multiobjective optimization. Fuel consumption and tear-and-wear on the thrusters are chosen as objectives. Multiobjective feasibility enhanced particle swarm optimization algorithm (MOFEPSO) is applied to find the Pareto set of this problem. An additional decision-making procedure, the technique of order preference by similarity to ideal solution (TOPSIS) is utilized to choose the final compromise solution in phase-II. The self-organizing map (SOM) technique is undertaken to mine the Pareto data set. A Remote Operated Vehicle (ROV) example is provided for illustrating the above analysis process. The effects of relative importance between objectives upon characteristics of thrust allocation are studied. The trajectories of decision variables and objectives are examined through the SOM method. Results from numerical examples demonstrate that the multiobjective optimization method together with decision-making skills can extend the application of optimization in the thrust allocation field. The findings in this work add to the understanding of relationships among several aspects of DPS.