Research on optimal scheduling of workshop equipment maintenance based on Quantum genetic Algorithm

Abstract

In the production process, production scheduling and equipment maintenance are interactive. But in theoretical research, equipment maintenance and production scheduling are usually separated. In order to consider the influence of production scheduling caused by equipment maintenance, an integrated model of workshop equipment maintenance and workshop scheduling is established in this paper. Based on the description of the workshop scheduling problem and its scheduling method, an improved quantum genetic algorithm (QGA) is proposed and used to solve the scheduling problem. In the improved quantum genetic algorithm, the tabu search algorithm is used to select chromosomes for coding, and the dynamic quantum rotation gate update mechanism is used. The rotation angle is adaptively adjusted, which makes the algorithm better converge to the global optimal solution. The experimental results show that compared with results of the without preventive maintenance, the integrated scheduling time and cost of quantum genetic algorithm are reduced by 15.22% and 27.52%; compared with the results of genetic algorithm, they are reduced by 9.77% and 17.9%. The result of simulation experiment shows that using quantum genetic algorithm to solve the production line scheduling problem is effective.