A computational study of a decomposition approach for the dynamic two-level uncapacitated facility location problem with single and multiple allocation.
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Date
2021
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Abstract
This work presents a computational study for two variants of a dynamic or multi-period two-level uncapacitated
facility location problem. In this problem, first-level plants serve different demand patterns of scattered clients
over a planning horizon via second-level facilities. In the first variant, second-level facilities can be supplied
by only one of the plants (single assignment); whereas, in the second, they can be served by more than one
of the first-level plants (multiple allocation). As the demands vary over time, the different operating settings
for plants and facilities, and client assignments need to be sought in each period to serve demands at minimal
installation and transportation costs. Since both problem variants arise naturally in the context of logistics
systems, it is of interest to have solution methods at hand for practitioners and researchers. To provide such
a tool, this work presents an efficient decomposition approach to solve the two problem variants. It relies
on Benders decomposition reformulations combined with a greedy randomized adaptive search procedure and
different Benders cut separation procedures. The devised solution framework outperformed CPLEX and its
Benders built-in algorithm on solving two different challenging large-scale instance sets.
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Keywords
Discrete location, Benders decomposition method, Benders optimality cuts
Citation
OLIVEIRA, P. B. de et al. A computational study of a decomposition approach for the dynamic two-level uncapacitated facility location problem with single and multiple allocation. Computers & Industrial Engineering, v. 151, artigo 106964, 2021. Disponível em: <https://www.sciencedirect.com/science/article/abs/pii/S0360835220306379>. Acesso em: 12 set. 2021.