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An interactive approximation algorithm for multi-objective integer programs

Research output: Contribution to journalArticle

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An interactive approximation algorithm for multi-objective integer programs. / Lokman, Banu; Koksalan, Murat; Korhonen, Pekka J.; Wallenius, Jyrki.

In: Computers & Operations Research, Vol. 96, 08.2018, p. 80-90.

Research output: Contribution to journalArticle

Harvard

Lokman, B, Koksalan, M, Korhonen, PJ & Wallenius, J 2018, 'An interactive approximation algorithm for multi-objective integer programs', Computers & Operations Research, vol. 96, pp. 80-90. https://doi.org/10.1016/j.cor.2018.04.005

APA

Lokman, B., Koksalan, M., Korhonen, P. J., & Wallenius, J. (2018). An interactive approximation algorithm for multi-objective integer programs. Computers & Operations Research, 96, 80-90. https://doi.org/10.1016/j.cor.2018.04.005

Vancouver

Lokman B, Koksalan M, Korhonen PJ, Wallenius J. An interactive approximation algorithm for multi-objective integer programs. Computers & Operations Research. 2018 Aug;96:80-90. https://doi.org/10.1016/j.cor.2018.04.005

Author

Lokman, Banu ; Koksalan, Murat ; Korhonen, Pekka J. ; Wallenius, Jyrki. / An interactive approximation algorithm for multi-objective integer programs. In: Computers & Operations Research. 2018 ; Vol. 96. pp. 80-90.

Bibtex

@article{345c0ab3773444d18d6daae3d56f04bb,
title = "An interactive approximation algorithm for multi-objective integer programs",
abstract = "We develop an interactive algorithm that approximates the most preferred solution for any multi-objective integer program with a desired level of accuracy, provided that the decision maker's (DM's) preferences are consistent with a nondecreasing quasiconcave value function. Using pairwise comparisons of the DM, we construct convex cones and eliminate the inferior regions that are close to being dominated by the cones in addition to the regions dominated by the cones. The algorithm allows the DM to change the desired level of accuracy during the solution process. We test the performance of the algorithm on a set of multi-objective combinatorial optimization problems. It performs very well in terms of the quality of the solution found, the solution time, and the required preference information.",
author = "Banu Lokman and Murat Koksalan and Korhonen, {Pekka J.} and Jyrki Wallenius",
year = "2018",
month = "8",
doi = "10.1016/j.cor.2018.04.005",
language = "English",
volume = "96",
pages = "80--90",
journal = "Computers & Operations Research",
issn = "0305-0548",
publisher = "Elsevier Limited",

}

RIS

TY - JOUR

T1 - An interactive approximation algorithm for multi-objective integer programs

AU - Lokman, Banu

AU - Koksalan, Murat

AU - Korhonen, Pekka J.

AU - Wallenius, Jyrki

PY - 2018/8

Y1 - 2018/8

N2 - We develop an interactive algorithm that approximates the most preferred solution for any multi-objective integer program with a desired level of accuracy, provided that the decision maker's (DM's) preferences are consistent with a nondecreasing quasiconcave value function. Using pairwise comparisons of the DM, we construct convex cones and eliminate the inferior regions that are close to being dominated by the cones in addition to the regions dominated by the cones. The algorithm allows the DM to change the desired level of accuracy during the solution process. We test the performance of the algorithm on a set of multi-objective combinatorial optimization problems. It performs very well in terms of the quality of the solution found, the solution time, and the required preference information.

AB - We develop an interactive algorithm that approximates the most preferred solution for any multi-objective integer program with a desired level of accuracy, provided that the decision maker's (DM's) preferences are consistent with a nondecreasing quasiconcave value function. Using pairwise comparisons of the DM, we construct convex cones and eliminate the inferior regions that are close to being dominated by the cones in addition to the regions dominated by the cones. The algorithm allows the DM to change the desired level of accuracy during the solution process. We test the performance of the algorithm on a set of multi-objective combinatorial optimization problems. It performs very well in terms of the quality of the solution found, the solution time, and the required preference information.

U2 - 10.1016/j.cor.2018.04.005

DO - 10.1016/j.cor.2018.04.005

M3 - Article

VL - 96

SP - 80

EP - 90

JO - Computers & Operations Research

T2 - Computers & Operations Research

JF - Computers & Operations Research

SN - 0305-0548

ER -

ID: 13066322