Open AccessResearch on FJSP Rescheduling Execution Cost Based on Modified Genetic Algorithm
Author(s) -
Qicai Zhou,
Yangrui Huang,
Xiang Xiong,
Junqiao Zhao
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/842/1/012025
Subject(s) - executable , correctness , computer science , schedule , genetic algorithm , job shop , process (computing) , plan (archaeology) , mathematical optimization , job shop scheduling , algorithm , flow shop scheduling , operating system , mathematics , machine learning , archaeology , history
In order to achieve dynamic production of smart plants, it is necessary to dynamically adjust schedule for disturbances in the manufacturing process. An executable optimized rescheduling plan needs developing, so the study of rescheduling cost is necessary. Based on the essential analysis of the rescheduling problem, a new flexible job shop rescheduling execution cost is proposed. The correctness of the execution cost is illustrated by the application in a modified genetic algorithm. The result shows that the rescheduling method with the execution cost as the fitness can generate a new plan with less deviation from the original schedule, which has a great significance for actual manufacturing.