Parameter selection in synchronous and asynchronous deterministic particle swarm optimization for ship hydrodynamics problems

Deterministic optimization algorithms are very attractive when the objective function is computation-ally expensive and therefore the statistical analysis of the optimization outcomes becomes too expensive. Among deterministic methods, deterministic particle swarm optimization (DPSO) has several attractive characteristics such as the simplicity of the heuristics, the ease of implementation, and its often fairly remarkable effectiveness. The performances of DPSO depend on four main setting parameters: the num-ber of swarm particles, their initialization, the set of coefficients defining the swarm behavior, and (for box-constrained optimization) the method to handle the box constraints. Here, a parametric study ofDPSO is presented, with application to simulation-based design in ship hydrodynamics. The objective isthe identification of the most promising setup for both synchronous and asynchronous implementationsof DPSO. The analysis is performed under the assumption of limited computational resources and largecomputational burden of the objective function evaluation. The analysis is conducted using 100 analyt-ical test functions (with dimensionality from two to fifty) and three performance criteria, varying theswarm size, initialization, coefficients, and the method for the box constraints, resulting in more than 40,000 optimizations. The most promising setup is applied to the hull-form optimization of a high speedcatamaran, for resistance reduction in calm water and at fixed speed, using a potential-flow solver.