An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem
Joint Authors
Xia, Beixin
Peng, Yunfang
Zeng, Tian
Fan, Lingzhi
Han, Yajuan
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-05
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
This paper deals with stochastic dynamic facility layout problem under demand uncertainty in terms of material flow between facilities.
A robust approach suggests a robust layout in each period as the most frequent one falling within a prespecified percentage of the optimal solution for multiple scenarios.
Mont Carlo simulation method is used to randomly generate different scenarios.
A mathematical model is established to describe the dynamic facility layout problem with the consideration of transport device assignment.
As a solution procedure for the proposed model, an improved adaptive genetic algorithm with population initialization strategy is developed to reduce the search space and improve the solving efficiency.
Different sized instances are compared with Particle Swarm Optimization (PSO) algorithm to verify the effectiveness of the proposed genetic algorithm.
The experiments calculating the cost deviation ratio under different fluctuation level show the good performance of the robust layout compared to the expected layout.
American Psychological Association (APA)
Peng, Yunfang& Zeng, Tian& Fan, Lingzhi& Han, Yajuan& Xia, Beixin. 2018. An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem. Discrete Dynamics in Nature and Society،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1152267
Modern Language Association (MLA)
Peng, Yunfang…[et al.]. An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem. Discrete Dynamics in Nature and Society No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1152267
American Medical Association (AMA)
Peng, Yunfang& Zeng, Tian& Fan, Lingzhi& Han, Yajuan& Xia, Beixin. An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem. Discrete Dynamics in Nature and Society. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1152267
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1152267