An improved algorithm exploiting the characteristics of a distance-based preference function to converge to preferred solutions
We address the problem of choosing the most preferred of a set of alternatives that are defined by multiple criteria. We assume that the decision maker’s preferences can be represented by a general class of weighted distance functions that can take a wide variety of forms. We exploit the characteris...
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| Published in: | European journal of operational research |
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| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
01.08.2025
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| ISSN: | 0377-2217 |
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| Abstract | We address the problem of choosing the most preferred of a set of alternatives that are defined by multiple criteria. We assume that the decision maker’s preferences can be represented by a general class of weighted distance functions that can take a wide variety of forms. We exploit the characteristics of these functions and develop an interactive algorithm that guarantees to find the most preferred alternative of a decision maker whose preferences are consistent with a distance-based function. In contrast with a benchmark algorithm that uses similar preference functions, our algorithm moves through different distance functions effectively to converge to the best alternative quickly. Our experiments on a variety of three- and four-objective problems demonstrate that our algorithm performs well, far outperforming the benchmark algorithm in terms of the required preference information from the decision maker.
•Addresses choice problems considering distance-based preference functions.•Exploits the characteristics of distance-based functions during the search process.•Moves through different distance-based functions effectively.•Converges to the most preferred solution quickly.•Outperforms a benchmark algorithm in required preference information. |
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| AbstractList | We address the problem of choosing the most preferred of a set of alternatives that are defined by multiple criteria. We assume that the decision maker’s preferences can be represented by a general class of weighted distance functions that can take a wide variety of forms. We exploit the characteristics of these functions and develop an interactive algorithm that guarantees to find the most preferred alternative of a decision maker whose preferences are consistent with a distance-based function. In contrast with a benchmark algorithm that uses similar preference functions, our algorithm moves through different distance functions effectively to converge to the best alternative quickly. Our experiments on a variety of three- and four-objective problems demonstrate that our algorithm performs well, far outperforming the benchmark algorithm in terms of the required preference information from the decision maker.
•Addresses choice problems considering distance-based preference functions.•Exploits the characteristics of distance-based functions during the search process.•Moves through different distance-based functions effectively.•Converges to the most preferred solution quickly.•Outperforms a benchmark algorithm in required preference information. |
| Author | Karakaya, G. Köksalan, M. |
| Author_xml | – sequence: 1 givenname: G. surname: Karakaya fullname: Karakaya, G. email: kgulsah@metu.edu.tr organization: Department of Business Administration, Middle East Technical University, 06800 Ankara, Turkey – sequence: 2 givenname: M. orcidid: 0000-0002-5423-3905 surname: Köksalan fullname: Köksalan, M. organization: Ross School of Business, University of Michigan, Ann Arbor, MI 48109, USA |
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| Cites_doi | 10.1016/j.ejor.2017.07.028 10.1287/mnsc.30.11.1336 10.1016/0377-2217(81)90275-7 10.1016/j.ejor.2022.11.043 10.1016/j.trb.2025.103162 10.1080/24725854.2019.1670373 10.1016/j.ejor.2010.02.027 10.1142/S0219622020500510 10.1287/mnsc.41.7.1158 10.1007/s10479-014-1545-2 10.1007/s10479-014-1669-4 10.1007/s10898-012-9955-7 10.1057/jors.1991.80 10.1287/opre.28.3.785 |
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| References | Karakaya, Şakar (b7) 2021; 20 Prinz, Ruzika (b13) 2024 Silberberg, Suen (b14) 2001 Köksalan, Sagala (b8) 1995; 41 Lokman, Köksalan (b10) 2013; 57 Karakaya, Köksalan (b4) 2020; 52 Korhonen, Wallenius, Zionts (b9) 1984; 30 Zionts (b17) 1981; 7 Fowler, Gel, Köksalan, Korhonen, Marquis, Wallenius (b2) 2010; 206 Taner, Köksalan (b15) 1991; 42 Nicholson, Snyder (b12) 2008 Zionts, Wallenius (b18) 1980; 28 Chinneck (b1) 2008 Karakaya, Köksalan (b3) 2016; 245 Karakaya, Köksalan (b5) 2023; 308 Lokman, Köksalan, Korhonen, Wallenius (b11) 2016; 245 Tureci-Isik, Köksalan, Tezcaner-Öztürk (b16) 2025; 193 Karakaya, Köksalan, Ahipaşaoğlu (b6) 2018; 265 Chinneck (10.1016/j.ejor.2025.08.036_b1) 2008 Lokman (10.1016/j.ejor.2025.08.036_b10) 2013; 57 Karakaya (10.1016/j.ejor.2025.08.036_b7) 2021; 20 Taner (10.1016/j.ejor.2025.08.036_b15) 1991; 42 Karakaya (10.1016/j.ejor.2025.08.036_b3) 2016; 245 Zionts (10.1016/j.ejor.2025.08.036_b17) 1981; 7 Korhonen (10.1016/j.ejor.2025.08.036_b9) 1984; 30 Tureci-Isik (10.1016/j.ejor.2025.08.036_b16) 2025; 193 Fowler (10.1016/j.ejor.2025.08.036_b2) 2010; 206 Nicholson (10.1016/j.ejor.2025.08.036_b12) 2008 Prinz (10.1016/j.ejor.2025.08.036_b13) 2024 Zionts (10.1016/j.ejor.2025.08.036_b18) 1980; 28 Köksalan (10.1016/j.ejor.2025.08.036_b8) 1995; 41 Silberberg (10.1016/j.ejor.2025.08.036_b14) 2001 Karakaya (10.1016/j.ejor.2025.08.036_b4) 2020; 52 Karakaya (10.1016/j.ejor.2025.08.036_b6) 2018; 265 Karakaya (10.1016/j.ejor.2025.08.036_b5) 2023; 308 Lokman (10.1016/j.ejor.2025.08.036_b11) 2016; 245 |
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| SubjectTerms | Exact algorithm Interactive algorithm Most preferred solution Multiple objective programming |
| Title | An improved algorithm exploiting the characteristics of a distance-based preference function to converge to preferred solutions |
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