Dynamic scheduling of flexible job shop based on genetic algorithm

Author

Yu, Tianbiao ; Zhou, Jing ; Fang, Junhua ; Gong, Yadong ; Wang, Wanshan

Author_Institution

Sch. of Mech. Eng. & Autom., Northeastern Univ., Shenyang

fYear

2008

fDate

1-3 Sept. 2008

Firstpage

2014

Lastpage

2019

Abstract

Using genetic algorithm to resolve dynamic production scheduling problem of flexible job shop is presented. A math model and objective function for dynamic scheduling of flexible job shop is set up by analysis problem of flexible job shop scheduling and restrictive condition is research. A genetic operator that can meet the need of production scheduling of flexible job shop is designed based on working procedure coding. Coding, crossover, mutation, fitness calculation, controls parameter selection and stop condition is studied. Based on those simulation is carry out and the result of it show correctness and validity of arithmetic.

Keywords

dynamic scheduling; genetic algorithms; job shop scheduling; dynamic flexible job shop scheduling; dynamic production scheduling problem; fitness calculation; genetic algorithm; math model; objective function; parameter selection; restrictive condition; stop condition; working procedure coding; Automation; Dynamic scheduling; Genetic algorithms; Genetic mutations; Job design; Job production systems; Job shop scheduling; Logistics; Mechanical engineering; Production systems; Flexible job shop; Genetic algorithm; Production scheduling; Simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4244-2502-0

Electronic_ISBN

978-1-4244-2503-7

Type

conf

DOI

10.1109/ICAL.2008.4636493

Filename

4636493