Job-shop scheduling optimization design based on an improved GA

Author

Zhao, Zixiang ; Zhang, Guoshan ; Bing, Zhigang

Author_Institution

Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China

fYear

2012

fDate

6-8 July 2012

Firstpage

654

Lastpage

659

Abstract

The job-shop scheduling problem (JSP) is a hard combinatorial optimization problem. In this paper, the mixed programming of MATLAB and VC is considered to solve the JSP. Firstly, MATLAB is used to implement an improved genetic algorithm (GA), and then the program is packaged into a dynamic link library (DLL). Secondly, VC is used to realize the input/output interface and call the GA DLL to schedule and store the scheduling results into the ORACLE database. Finally, the simulation results show that the improved GA has good optimization performance in solving JSP and the mixed programming design is effective.

Keywords

C language; combinatorial mathematics; design; genetic algorithms; job shop scheduling; object-oriented databases; relational databases; software libraries; visual languages; GA DLL; MATLAB; ORACLE database; VC; dynamic link library; genetic algorithm; hard combinatorial optimization problem; input-output interface; job-shop scheduling optimization design; mixed programming design; Biological cells; Genetic algorithms; Job shop scheduling; MATLAB; Optimal scheduling; Sociology; Genetic Algorithm (GA); Job-shop Scheduling Problem (JSP); Mixed Programming of MATLAB and VC++; Scheduling Optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2012 10th World Congress on

Conference_Location

Beijing

Print_ISBN

978-1-4673-1397-1

Type

conf

DOI

10.1109/WCICA.2012.6357960

Filename

6357960