A Job Shop Scheduling Method Based on Ant Colony Algorithm

Abstract

The problem of job shop scheduling is a hot research topic nowadays. How to improve the production efficiency of the equipment and shorten the processing time of the workpieces has become an important research work. The parallelism and mechanism of distributed computing of Ant colony optimization (ACO) provide a good solution in solving job shop scheduling problems. In this paper, the ACO is applied to the job shop scheduling of industrial production. And the ACO is used to solve the scheduling problem, the pheromone update strategy in the ant colony algorithm has been modified, and roulettes wheel was introduced. On the basis of above modifications, a job shop scheduling method based on ant colony algorithm has been used in this paper. In addition, the disjunction graph model of the job shop problem has been also established in this paper, which turned the job shop scheduling problem into a solution to the traveling salesman problem and then redefined as a natural expression model suitable for ant colony algorithm. When solving the traveling salesman problem, virtual nodes were added as the super source and destination in the search process, the distance between cities and the shortest path in the traveling salesman were corresponded with the processing time and the shortest processing time in the job shop scheduling problem one by one. In this paper, C++ has been used for programming, and the FT06 data example was used as a test example. In the experiment, the scheme of job scheduling with minimum total completion time was obtained successfully, which verified the feasibility and effectiveness of this method in the shop scheduling problem.