A Hybrid Particle Swarm Optimization for Parallel Machine Scheduling with Shared and Multi-mode Resources

In this paper, we present a parallel machine scheduling with shared and multi-mode resources (PMS-SMR) problem which is widely encountered in manufacturing engineering. The integer programming for this problem is given and a hybrid particle swarm optimization (HPSO) algorithm is put forward with a problem-based solution representation and a balancing optimization (BO)-based local search. The HPSO algorithm can be applied to obtain the best permutation of the fitness function with least-makespan optimization criterion. Experimental results show that it is feasible and effective, especially in solving large-scale problems.

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