Threshold-Based Particle Comparison Criterion for Multi-Objective Constrained Optimization

A threshold-based particle comparison criterion for handling multi-objective constrained optimization problems, which retains infeasible solution particles with small ordinal values and constraint violations within acceptable ranges, facilitating evolution from infeasible to feasible solutions. A novel crowding distance function assigns higher values to points in sparse regions and near Pareto front boundaries, increasing their selection probability, constituting a hybrid particle swarm optimization algorithm for solving multi-objective constrained optimization problems.