RESULTS OF THE OPTIMIZATION USING GOLDFISH FRAMEWORK

In this paper, a multi-objective version of the recent Constraint Multi-Swarm Particle Swarm Optimization without Velocity (CMPSOWV) is developed.  With the focus on wider adoption of optimization aimed at solving multi-objective constrained engineering design problems in practice, the proposed method is implemented in the popular Grasshopper framework as a new optimization plug-in “Goldfish”.  As CMPSOWV, the MOCMPSOWV algorithm is supposed to obtain highly diversified optimization results thanks to incorporating the multi-swarm approach and the enlarged search scope for the best solution in the multiple locations of the hyperspace.  The introduced MOCMPSOWV algorithm in the Goldfish framework has proven its superiority over algorithms such as: MOPSO, NSGA-II, SPEA, SPEA2, MOGA, MOEA/D in the quality of solution criteria and computing time in the engineering design problems such as: Welded beam case, Pressure Vessel case and multi-objective test functions.