Parallel Tasks Optimization Scheduling in Cloud Manufacturing System

Authors

Chenwei Feng, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;
Wang Yan, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;

Abstract

Abstract: To solve the problem of unbalanced resource requirements and low resource utilization when the same type of tasks are executed in parallel in the cloud manufacturing system, a task resource scheduling model with the goal of minimizing cost, minimizing time, maximizing reliability and optimizing quality is established. A non-dominated sorting genetic algorithm based on reference points (NSGA-III) is adopted to solve the model by combining real number matrix coding and crossover and mutation based on real number coding instead of common evolutionary strategy. And an optimal decision strategy based on combination of analytic hierarchy process and entropy value method is used to evaluate the solutions. The performance of the scheduling system with sufficient and limited resources is discussed respectively. The example proves that method is feasible.

Recommended Citation

Feng, Chenwei and Yan, Wang (2019) "Parallel Tasks Optimization Scheduling in Cloud Manufacturing System," Journal of System Simulation: Vol. 31: Iss. 12, Article 8.
DOI: 10.16182/j.issn1004731x.joss.19-FZ0275
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss12/8

First Page

2626

Revised Date

2019-07-02

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-FZ0275

Last Page

2635

CLC

TP391.9

Recommended Citation

Feng Chenwei, Wang Yan. Parallel Tasks Optimization Scheduling in Cloud Manufacturing System[J]. Journal of System Simulation, 2019, 31(12): 2626-2635.

DOI

10.16182/j.issn1004731x.joss.19-FZ0275