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A Generalized Ant Colony Algorithm for Job-shop Scheduling Problem

ZHANG Hong-guo;GONG Xue;School of Software,Harbin University of Science and Technology;School of Computer Science and Technology,Harbin University of Science and Technology;  
Aiming at the problem of ant colony algorithm for solving Job-shop scheduling problem.Considering the complexity of the algorithm that uses disjunctive graph to describe the relationship between workpiece processing.To solve the problem of optimal solution,a generalized ant colony algorithm is proposed.Under the premise of considering constrained relationship between equipment and process,the pheromone update mechanism is applied to solve Job-shop scheduling problem,so as to improve the quality of the solution.In order to improve the search efficiency,according to the state transition rules of ant colony algorithm,this paper makes a detailed study on the selection and improvement of the parameters in the algorithm,and designs the pheromone update strategy.Experimental results show that a generalized ant colony algorithm is more feasible and more effective.Compared with other algorithms in the literature,the results prove that the algorithm improves in computing the optimal solution and convergence speed.
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