Optimization for Unrelated Parallel Machine Scheduling with Deteriorating Jobs

Authors

Xuan Hua, 1.School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China; ;
Yingying Qin, 1.School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China; ;
Xueyuan Wang, 1.School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China; ;
Bailin Zhang, 2.Inspur Electronic Information Industry Co., Ltd, Ji’nan 250101, China;;

Abstract

Abstract: Unrelated parallel machine scheduling problem with deteriorating jobs is studied with the objective of minimizing the maximum completion time. The processing time of a job varies with its beginning time which is denoted as an increasing function of its starting time. It is assumed that each job has its own different deterioration rate on each machine. A mathematical programming model is formulated for the NP-hard problem. An improved genetic algorithm based on two segment coding and self-adaptive adjustment of genetic parameters is then designed to make job scheduling and machine allocation more reasonable. Through the simulation experiments of different sized problems, the results show that the proposed algorithm has more advantages in both resolution time and solution quality.

Recommended Citation

Hua, Xuan; Qin, Yingying; Wang, Xueyuan; and Zhang, Bailin (2019) "Optimization for Unrelated Parallel Machine Scheduling with Deteriorating Jobs," Journal of System Simulation: Vol. 31: Iss. 5, Article 12.
DOI: 10.16182/j.issn1004731x.joss.17-0150
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss5/12

First Page

919

Revised Date

2017-07-09

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.17-0150

Last Page

924

CLC

TP15;TB49;TN911

Recommended Citation

Xuan Hua, Qin Yingying, Wang Xueyuan, Zhang Bailin. Optimization for Unrelated Parallel Machine Scheduling with Deteriorating Jobs[J]. Journal of System Simulation, 2019, 31(5): 919-924.

DOI

10.16182/j.issn1004731x.joss.17-0150