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- W2794175087 abstract "Abstract Let N be the line-set and M be the column-set of a matrix { a i j } , such that a i j = 1 if line i ∈ N is covered by column j ∈ M , or a i j = 0 otherwise. Besides, let b j ≥ 0 be the benefit associated with a column j ∈ M . Given a constant T | M | , the NP-Hard Maximal Covering Location Problem (MCLP) consists in finding a subset X ⊆ M with the maximum sum of benefits, such that | X | ≤ T and every line in N is covered by at least one column in X. In this study, we investigate the min-max regret Maximal Covering Location Problem, a robust counterpart of MCLP, where the benefit of each column is uncertain and modeled as an interval data. The objective is to find a robust solution that minimizes the maximal regret over all possible combinations of values for the columns benefit. This problem has applications in disaster relief. We propose a MILP formulation, an exact and 2-approximation algorithms, and test them using classical instances from the literature." @default.
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- W2794175087 date "2018-02-01" @default.
- W2794175087 modified "2023-10-18" @default.
- W2794175087 title "Formulation and algorithms for the robust maximal covering location problem" @default.
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- W2794175087 doi "https://doi.org/10.1016/j.endm.2018.01.016" @default.
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