Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195616
Authors: 
Moslemipour, Ghorbanali
Year of Publication: 
2018
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 14 [Year:] 2018 [Issue:] 2 [Pages:] 429-442
Abstract: 
This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density function and covariance that change from period to period at random. To solve the proposed model, a novel hybrid intelligent algorithm is proposed by combining the simulated annealing and clonal selection algorithms. The proposed model and the hybrid algorithm are verified and validated using design of experiment and benchmark methods. The results show that the hybrid algorithm has an outstanding performance from both solution quality and computational time points of view. Besides, the proposed model can be used in both of the stochastic and deterministic situations.
Subjects: 
Clonal selection
Simulated annealing
Stochastic dynamic
Facility layout problem
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
Social Media Mentions:

Files in This Item:
File
Size
886.91 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.