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A hybrid algorithm of converse ant colony optimization (HCACO) is proposed, which is used to overcome the disadvantages of the slow convergence speed and stagnation behavior when solving job shop problem (JSP). In order to improve the probability of escaping from the local optimization, we induct converse ants into the ant colony. At the same time, each solution of ACO with certain probability pursues...
A hybrid algorithm of particle swarm optimization (PSO) and simulated annealing (SA) algorithm (HPSOSA) is proposed, which is used to overcome the deficiency of resolving job shop problem (JSP) and improve the quality of searching solutions. According to the characteristics of random and large-scale search of PSO, we adopt PSO to construct the parallel initial solutions of SA. At the same time, we...
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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