A hybrid CS-SA intelligent approach to solve uncertain dynamic facility layout problems considering dependency of demands

Artikel

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Journal of Industrial Engineering International ; ISSN: 2251-712X ; Volume: 14 ; Year: 2018 ; Issue: 2 ; Pages: 429-442 ; Heidelberg: Springer

Klassifikation und Themen

• Klassifikation: Management
• Thema: Clonal selection ; Simulated annealing ; Stochastic dynamic ; Facility layout problem

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Moslemipour, Ghorbanali
• Ereignis: Veröffentlichung
• (wer): Springer
• (wo): Heidelberg
• (wann): 2018

Weitere Informationen

• DOI: doi:10.1007/s40092-017-0222-x
• Handle: http://hdl.handle.net/10419/195616
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ