Based on Tabu Search and Particle Swarm Optimization Algorithms Solving Job Shop Scheduling Optimization Problems

Solving the Job shop Scheduling problem, the design is based on Particle Swarm Optimization and Taboo Search which is a fast algorithm, And in this algorithm, bring in particle swarm strategy and taboo search strategy, A hybrid intelligence algorithm based on Particle Swarm algorithm and the taboo Search algorithm(TS-PSO) is designed. It overcomes particle swarm optimization algorithm in solving combinatorial optimization problem, and better to avoid the tabu search algorithm falling into local optimum, and convergence speed has also been increased. Through particle swarm and taboo search algorithm combined, the results show that this algorithm has very good accuracy of convergence, and is feasible, and compared with the traditional scheduling algorithm, Embodies the obvious superiority.

I. Introduction

With the development of intelligent technology, more and more bionic intelligent optimization algorithm has been applied to the Job shop scheduling problem, and has got many good results. Because the single intelligent algorithm has its own insurmountable defects, the hybrid intelligent algorithm can compensate for each other's deficiencies, that composites and uses the Particle Swarm Optimization algorithm and tabu search algorithm, the advantages of the mixed tabu search of particle swarm optimization algorithm is proposed. At the same time in order to further solve the algorithm of the optimal solution, the two algorithms are analyzed, designed the comprehensive algorithm based on these two algorithms. So it overcomes the drawback of two algorithms, realizes the complementary advantages, makes the algorithm more vitality.