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

摘要

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.