Genetic Algorithm for Solving Multi-Objective Dynamic Flexible Job Shop Scheduling

Authors

Wang Chun, Institute of Electrical Automation, Jiangnan University, Wuxi 214122, China;
Zhang Ming, Institute of Electrical Automation, Jiangnan University, Wuxi 214122, China;
Zhicheng Ji, Institute of Electrical Automation, Jiangnan University, Wuxi 214122, China;
Wang Yan, Institute of Electrical Automation, Jiangnan University, Wuxi 214122, China;

Abstract

Abstract: To solve the scheduling problem of mold workshop in a toy factory with dynamic and flexible features, a mathematical model was established by introducing virtual operation and virtual working hours. Based on the strategies of periodic scheduling combined with dynamic event scheduling as well as the rolling window scheduling operation technology, dynamic scheduling was transformed into several continuous static scheduling windows, under which multi-objective genetic algorithm was used to solve the model. The priority of operation scheduling was given in different dynamic events. In addition, the encoding and anti-encoding of chromosome's operation sequence were made based on the proposed priority. Real running of mold workshop scheduling verifies the effectiveness of the proposed dynamic scheduling model, scheduling policy and the algorithm.

Recommended Citation

Chun, Wang; Ming, Zhang; Ji, Zhicheng; and Yan, Wang (2020) "Genetic Algorithm for Solving Multi-Objective Dynamic Flexible Job Shop Scheduling," Journal of System Simulation: Vol. 29: Iss. 8, Article 3.
DOI: 10.16182/j.issn1004731x.joss.201708003
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss8/3

First Page

1647

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201708003

Last Page

1657

CLC

TP183

Recommended Citation

Wang Chun, Zhang Ming, Ji Zhicheng, Wang Yan. Genetic Algorithm for Solving Multi-Objective Dynamic Flexible Job Shop Scheduling[J]. Journal of System Simulation, 2017, 29(8): 1647-1657.

DOI

10.16182/j.issn1004731x.joss.201708003