Multi-Objective Particle Swarm Optimization MATLAB Program
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Resource Overview
MATLAB implementation of multi-objective particle swarm optimization featuring two objective functions (f1 and f2) using a weighted sum approach for solution convergence
Detailed Documentation
This MATLAB program implements multi-objective particle swarm optimization (MOPSO) with two distinct objective functions, f1 and f2. The algorithm employs a weighted sum method to combine these objectives into a single fitness function, allowing for comprehensive optimization across multiple criteria. The implementation includes particle position updates, velocity calculations, and personal/global best tracking mechanisms typical of PSO algorithms. Key functions handle objective function evaluation, weight adjustment, and Pareto-front approximation. Through strategic weight assignment and iterative optimization, this program effectively balances competing objectives to generate superior multi-objective solutions. The code structure supports easy modification of objective functions and weight parameters for different optimization scenarios.
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