Multi-objective Particle Swarm Optimization (MOPSO)

Multi-objective Particle Swarm Optimization (MOPSO) is an algorithm inspired by the collective behavior of swarms, like birds or fish, to solve complex problems with multiple goals. Instead of aiming for a single best solution, MOPSO finds a set of optimal solutions that balance different objectives—these are called Pareto optimal solutions. It does this by maintaining a group of candidate solutions ("particles") that explore the problem space, sharing information and adjusting their positions over time to improve according to the multiple goals. This approach helps identify diverse, high-quality solutions in complex decision-making scenarios.