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http://hdl.handle.net/10609/84585
Title: Solving the deterministic and stochastic uncapacitated facility location problem: from a heuristic to a simheuristic
Author: Armas Adrián, Jésica de
Juan Pérez, Ángel Alejandro
Marquès Puig, Joan Manuel
Pedroso, João Pedro
Others: Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Universidade do Porto
Keywords: uncapacitated facility location problem
stochastic combinatorial optimization problems
metaheuristics
simheuristics
Issue Date: Oct-2017
Publisher: Journal of the Operational Research Society
Citation: de Armas, J., Juan, A.A., Marquès Puig, J. & Pedroso, J.P. (2017). Solving the deterministic and stochastic uncapacitated facility location problem: from a heuristic to a simheuristic. Journal of the Operational Research Society, 68(10), 1161-1176. doi: 10.1057/s41274-016-0155-6
Project identifier: info:eu-repo/grantAgreement/TRA2013-48180-C3-P
info:eu-repo/grantAgreement/TRA2015-71883-REDT
info:eu-repo/grantAgreement/2014-CTP-00001
Also see: https://link.springer.com/epdf/10.1057/s41274-016-0155-6
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.
Language: English
URI: http://hdl.handle.net/10609/84585
ISSN: 0160-5682MIAR

1476-9360MIAR
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