Paper Titles
Research on Engine Fault Detection System Based on Exhaust Emission
p.516
Teaching Transition for International Education from ‘Foreign Students Class’ to ‘International Class’: The Case of Materials Physics Courses
p.521
Study on Histocompatibility and Carcinogenicity of Silicone Gel-Filled Breast Implants after Radiation Sterilization
p.525
Study on Macroscopic Prediction Model of Traffic Accident Influence Factors
p.531
Identification of Nonlinear Property of Honeycomb Paperboard through Use of Hilbert Transform
p.536
Optimization of Flow Shop Scheduling Problem Using Differential Evolution and Variable Neighborhood Search
p.540
Mechatronics Education Curriculum for Nurturing Consumer Electronics Engineers Using LEGO Education Tools
p.545
Research on Green Manufacturing of Automotive Enterprises Based on Fuzzy Comprehensive Evaluation Method
p.551
Entropy-Enhanced Genetic Algorithm with Tabu Search for Job Shop Scheduling Problems
p.557

Optimization of Flow Shop Scheduling Problem Using Differential Evolution and Variable Neighborhood Search

Article Preview

Abstract:

This paper proposed a new differential evolution algorithm based on variable neighbourhood search which is called as VNSDE. In VNSDE, the operation of variable neighbourhood search is performed after three basic operations of differential evolution, which can enhance the global search and improve the convergence. VNSDE is applied for solving flow shop scheduling problem with the makespan criterion. Computational experiment is performed over a typical FSSP benchmark using VNSDE, GA and DE, and result shows that VNSDE has higher performance than GA and DE.

You might also be interested in these eBooks
Mechatronic Systems and Materials Application View Preview

Info:

Periodical:

Advanced Materials Research (Volume 590)

Pages:

540-544

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.590.540

Citation:

Cite this paper

Online since:

November 2012

Authors:

Yan Ping Zhou

Keywords:

Differential Evolution, Flow Shop Scheduling, Variable Neighborhood Search

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

References

[1] R. Storn and K. Price, Differential evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces, in: International Computer Science Institute, Technical Report TR-95-012, Berkley, (1995).

Google Scholar

[2] R. Storn and K. Price, Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces, J. Global. Optimiz. 11 (1997) 341-359.

Google Scholar

[3] Y. P. Zhou and X. S. Gu, Development of differential evolution algorithm, Control and Instruments in Chemical Industry. 34 (2007) 1-5.

Google Scholar

[4] N. Mladenovic and P. Hansen, Variable neighborhood search, Comput. Oper. Res. 24 (1997) 1097-1100.

Google Scholar

[5] P. Hansen and N. Mladenovic, Variable neighborhood search: principles and applications, European J. Oper. Res. 130 (2001) 449-467.

Google Scholar

[6] M. R. Garey and D. S. Johnson, The complexity of flowshop and jobshop scheduling, Math. Oper. Res. 1 (1976) 117-129.

Google Scholar

[7] E. Nowicki and C. Smutnicki, A fast tabu search algorithm for the permutation flowshop problem, European J. Oper. Res. 91 (1996) 160-175.

DOI: 10.1016/0377-2217(95)00037-2

Google Scholar

[8] T. Murata, H. Ishibuchi and H. Tanaka, Genetic algorithms for flowshop scheduling problems, Comput. Ind. Eng. 30 (1996) 1061-71.

Google Scholar

[9] O. Etiler, B. Toklu, M. Atak and J. Wilson, A genetic algorithm for flow shop scheduling problems, J. Opl. Res. Soc. 55 (2004) 830-835.

DOI: 10.1057/palgrave.jors.2601766

Google Scholar

[10] C. Rajendran and H. Ziegler, Ant-colony algorithms for permutation flowshop scheduling to minimize makespan / total flowtime of jobs, European J. Oper. Res. 155 (2004) 426-438.

DOI: 10.1016/s0377-2217(02)00908-6

Google Scholar

[11] B. Liu, L. Wang and Y. H. Jin, An effective PSO-based memetic algorithm for flow shop scheduling, IEEE Trans. Syst. Man Cybern. B 37 (2007) 18-27.

DOI: 10.1109/tsmcb.2006.883272

Google Scholar

[12] G. Onwubolu and D. Davendra, Scheduling flow shops using differential evolution algorithm, European J. Oper. Res. 171 (2006) 674-692.

DOI: 10.1016/j.ejor.2004.08.043

Google Scholar

[13] E. Tallad, Benchmarks for basic scheduling, European J. Oper. Res. 64 (1993) 278-285.

Google Scholar