Solving the deterministic and stochastic uncapacitated facility location problem: from a heuristic to a simheuristic
Jésica de Armas (),
Angel A. Juan (),
Joan M. Marquès () and
João Pedro Pedroso ()
Additional contact information
Angel A. Juan: Open University of Catalonia
Joan M. Marquès: Open University of Catalonia
João Pedro Pedroso: University of Porto
Journal of the Operational Research Society, 2017, vol. 68, issue 10, 1161-1176
Abstract The uncapacitated facility location problem (UFLP) is a popular combinatorial optimization problem with practical applications in different areas, from logistics to telecommunication networks. While most of the existing work in the literature focuses on minimizing total cost for the deterministic version of the problem, some degree of uncertainty (e.g., in the customers’ demands or in the service costs) should be expected in real-life applications. Accordingly, this paper proposes a simheuristic algorithm for solving the stochastic UFLP (SUFLP), where optimization goals other than the minimum expected cost can be considered. The development of this simheuristic is structured in three stages: (i) first, an extremely fast savings-based heuristic is introduced; (ii) next, the heuristic is integrated into a metaheuristic framework, and the resulting algorithm is tested against the optimal values for the UFLP; and (iii) finally, the algorithm is extended by integrating it with simulation techniques, and the resulting simheuristic is employed to solve the SUFLP. Some numerical experiments contribute to illustrate the potential uses of each of these solving methods, depending on the version of the problem (deterministic or stochastic) as well as on whether or not a real-time solution is required.
Keywords: uncapacitated facility location problem; stochastic combinatorial optimization problems; metaheuristics; simheuristics (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1057/s41274-016-0155-6 Abstract (text/html)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pal:jorsoc:v:68:y:2017:i:10:d:10.1057_s41274-016-0155-6
Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274
Access Statistics for this article
Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook
More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().