Optimization-based mechanism synthesis using multi-objective parallel asynchronous particle swarm optimization.

摘要

A distributed variant of multi-objective particle swarm optimization (MOPSO) called multi-objective parallel asynchronous particle swarm optimization (MOPAPSO) is presented, and the effects of distribution of objective function calculations to slave processors on the results and performance are investigated and employed for the synthesis of Grashof mechanisms.;MOPAPSO's ability to match MOPSO's results using parallelization for improved performance is presented. Results for both four and five bar mechanism synthesis examples are shown.;By using a formal multi-objective handling scheme based on Pareto dominance criteria, the need to pre-weight competing systemic objective functions is removed and the optimal solution for a design problem can be selected from a front of candidates after the parameter optimization has been completed.