Details
Original language | English |
---|---|
Pages (from-to) | 35-46 |
Number of pages | 12 |
Journal | European Journal of Operational Research |
Volume | 258 |
Issue number | 1 |
Publication status | Published - Apr 2017 |
Abstract
This paper is devoted to the study of unconstrained planar multiobjective location problems, where distances between points are defined by means of the Manhattan norm. We characterize the nonessential objectives and, by eliminating them, we develop an effective algorithm for generating the whole set of efficient solutions as the union of a special family of rectangles and line segments. We prove the correctness of this algorithm, analyze its complexity, and present illustrative computational results obtained by a MATLAB-based implementation.
Keywords
- Location problem, Manhattan norm, Multiple objective programming, Nonessential objective, Scalarization
ASJC Scopus subject areas
- Computer Science(all)
- General Computer Science
- Mathematics(all)
- Modelling and Simulation
- Decision Sciences(all)
- Management Science and Operations Research
- Decision Sciences(all)
- Information Systems and Management
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In: European Journal of Operational Research, Vol. 258, No. 1, 04.2017, p. 35-46.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - A new algorithm for solving planar multiobjective location problems involving the Manhattan norm
AU - Alzorba, Shaghaf
AU - Günther, Christian
AU - Popovici, Nicolae
AU - Tammer, Christiane
N1 - Funding information: N. Popovici’s work was supported by CNCS-UEFISCDI Romania, within the research project PN-II-ID-PCE-2011-3-0024 .
PY - 2017/4
Y1 - 2017/4
N2 - This paper is devoted to the study of unconstrained planar multiobjective location problems, where distances between points are defined by means of the Manhattan norm. We characterize the nonessential objectives and, by eliminating them, we develop an effective algorithm for generating the whole set of efficient solutions as the union of a special family of rectangles and line segments. We prove the correctness of this algorithm, analyze its complexity, and present illustrative computational results obtained by a MATLAB-based implementation.
AB - This paper is devoted to the study of unconstrained planar multiobjective location problems, where distances between points are defined by means of the Manhattan norm. We characterize the nonessential objectives and, by eliminating them, we develop an effective algorithm for generating the whole set of efficient solutions as the union of a special family of rectangles and line segments. We prove the correctness of this algorithm, analyze its complexity, and present illustrative computational results obtained by a MATLAB-based implementation.
KW - Location problem
KW - Manhattan norm
KW - Multiple objective programming
KW - Nonessential objective
KW - Scalarization
UR - http://www.scopus.com/inward/record.url?scp=85003678458&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2016.10.045
DO - 10.1016/j.ejor.2016.10.045
M3 - Article
VL - 258
SP - 35
EP - 46
JO - European Journal of Operational Research
JF - European Journal of Operational Research
SN - 0377-2217
IS - 1
ER -