Premium
Robust mean absolute deviation problems on networks with linear vertex weights
Author(s) -
LópezdelosMozos M.C.,
Puerto J.,
RodríguezChía A.M.
Publication year - 2013
Publication title -
networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.977
H-Index - 64
eISSN - 1097-0037
pISSN - 0028-3045
DOI - 10.1002/net.21471
Subject(s) - least absolute deviations , minimax , absolute deviation , robustness (evolution) , mathematics , vertex (graph theory) , regret , mathematical optimization , linear programming , robust optimization , computer science , algorithm , graph , combinatorics , statistics , biochemistry , chemistry , estimator , gene
Abstract This article deals with incorporating the mean absolute deviation objective function in several robust single facility location models on networks with dynamic evolution of node weights, which are modeled by means of linear functions of a parameter. Specifically, we have considered two robustness criteria applied to the mean absolute deviation problem: the MinMax criterion, and the MinMax regret criterion. For solving the corresponding optimization problems, exact algorithms have been proposed and their complexities have been also analyzed. © 2012 Wiley Periodicals, Inc. NETWORKS, 2013