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In the paper, we propose a hybrid algorithm ACOTS for improving the performance of intelligence optimization algorithm for solving job shop scheduling problems. In ACOTS algorithm, the ACO algorithm was applied to search in the global solution space, and TS algorithm was utilized as the local algorithm. This paper had not only proved the global asymptotic convergence of the hybrid algorithm by Markov...
To improve the performance of intelligence optimization algorithm for solving Job Shop Scheduling Problem ,a hybrid ant colony algorithm called tabu search and ant (TSANT) algorithm with global convergence was proposed. In the hybrid ant colony algorithm, the MMAS algorithm was applied to search in the global solution space, and the tabu search algorithm was utilized as the local algorithm. The global...
A hybrid particle swarm algorithm with global asymptotic convergence was proposed, which was used to make up for the deficiencies of resolving job shop scheduling problem. In the hybrid particle swarm algorithm, the particle swarm with optimum keeping strategy was applied to search in the global solution space, and the taboo search algorithm was utilized as the local algorithm, which can strengthen...
A new particle swarm algorithm is proposed to make up for the drawback of conventional one on solving job shop scheduling problem, and improve the performance of searching solutions. In the new algorithm, the particle swarm algorithm is adopted to search in the solution space globally. According to the feature of job shop problem solutions, a critical operation-based selection method is proposed,...
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