Research on Flexible Job Shop Scheduling Problem Based on Improved Genetic Algorithm
CAO Rui
HOU Xiangpan
JIN Siting
Abstract：This paper analyzes the characteristics of flexible job shop scheduling problem,and proposes an improved genetic algorithm to solve the problem. In the case of the maximum completion time as the performance index,a flexible shop scheduling method based on the improved algorithm is designed to change the population initialization method to improve the search efficiency, and combine the problem characteristics to design a reasonable chromosome coding method,crossover operator and mutation opera?tor to improve Solving efficiency. The feasibility and validity of the proposed initialization method are verified by experimental simu?lation.
Keywords：genetic algorithmflexible shop scheduling
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 285-288 )