基于禁忌搜索和粒子群算法求解作业车间调度优化问题

Liang Xu, Li Yanpeng, Jiao Xuan
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引用次数: 2

摘要

为解决作业车间调度问题,设计了一种基于粒子群优化和禁忌搜索的快速算法,并在该算法中引入了粒子群策略和禁忌搜索策略,设计了一种基于粒子群算法和禁忌搜索算法的混合智能算法(TS-PSO)。该算法在解决组合优化问题时克服了粒子群算法的缺点,更好地避免了禁忌搜索算法陷入局部最优,提高了收敛速度。通过粒子群算法和禁忌搜索算法的结合,结果表明该算法具有很好的收敛精度,并且是可行的,并且与传统的调度算法相比,体现出明显的优越性。
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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.
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