Research on Multi-objective Flexible Job Shop Scheduling Scheme Based on Discrete Particle Swarm Optimization

This paper proposes a multi-objective discrete particle swarm optimization algorithm (agsMODPSO) based on an adaptive grid strategy for Multi-objective flexible job shop scheduling problems taking into account production costs. The algorithm introduces the Pareto domination relation to evaluate particles, establishes an external archive set to store non-dominated solutions, and performs adaptive grid division on the external archive set. The external archive set is maintained by a mixed strategy of adaptive grid and crowding distance, and the global optimal solution is selected based on this strategy. Applying the agsMODPSO algorithm to a practical case for solving the problem demonstrated the feasibility and effectiveness of the algorithm.