Formulating and solving sustainable stochastic dynamic facility layout problem: a key to sustainable operations

Akash Tayal (), Angappa Gunasekaran (), Surya Prakash Singh (), Rameshwar Dubey and Thanos Papadopoulos ()
Additional contact information
Akash Tayal: Indira Gandhi Delhi Technical University for Women
Angappa Gunasekaran: University of Massachusetts
Surya Prakash Singh: Indian Institute of Technology Delhi
Thanos Papadopoulos: University of Kent

Annals of Operations Research, 2017, vol. 253, issue 1, No 27, 655 pages

Abstract: Abstract Facility layout design, a NP hard problem, is associated with the arrangement of facilities in a manufacturing shop floor, which impacts the performance, and cost of system. Efficient design of facility layout is a key to the sustainable operations in a manufacturing shop floor. An efficient layout design not only optimizes the cost and energy due to proficient handling but also increase flexibility and easy accessibility. Traditionally, it is solved using meta-heuristic techniques. But these algorithmic or procedural methodologies do not generate effective and efficient layout design from sustainable point of view, where design should consider multiple criteria such as demand fluctuations, material handling cost, accessibility, maintenance, waste and more. In this paper, to capture the sustainability in the layout design these parameters are considered, and a new sustainable stochastic dynamic facility layout problem (SDFLP) is formulated and solved. SDFLP is optimized for material handling cost and rearrangement cost using various meta-heuristic techniques. The pool of layouts thus generated are then analyzed by data envelopment analysis to identify efficient layouts. A novel hierarchical methodology of consensus ranking of layouts is proposed which combines the multiple attributes/criteria. Multi attribute decision-making techniques such as technique for order preference by similarity to ideal solution, interpretive ranking process and analytic hierarchy process, Borda–Kendall and integer linear programming based rank aggregation techniques are applied. To validate the proposed methodology data sets for facility size $$N=12$$ N = 12 for time period $$T=5$$ T = 5 having Gaussian demand are considered.

Keywords: Stochastic dynamic facility layout; Simulated annealing; Chaotic simulated annealing; TOPSIS; AHP; DEA; Borda–Kendall; Flow distance; Accessibility; Maintenance; Sustainable operations (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://link.springer.com/10.1007/s10479-016-2351-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:253:y:2017:i:1:d:10.1007_s10479-016-2351-9

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-016-2351-9

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().