An Interactive partitioning approach for multiobjective decision making under a general monotone utility function

Date

2013-09-01

Author

Karasakal, Esra

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

291
views

0
downloads

We develop an interactive partitioning approach for solving the multiobjective decision making problem of a decision maker (DM) who has an implicit general monotone utility function. The approach reduces feasible solution space using the DM's preferences. Hypothetical solutions called partition ideals (PIs) that dominate portions of the efficient frontier are generated and those that are inferior to a feasible solution are used to eliminate the dominated regions. We investigate the issues in representation of the reduced feasible solution space. We develop procedures for locating PIs and measuring the size of feasible solution space. We incorporate these ideas into an approach that converges to a neighborhood of the most preferred solution of the DM. We demonstrate the approach on an example problem.

Subject Keywords

Multiobjective decision making, Interactive approach

URI

https://hdl.handle.net/11511/49099

Journal

INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING

DOI

https://doi.org/10.1142/s0219622013400051

Collections

Department of Industrial Engineering, Article

Suggestions

OpenMETU
Core

An interactive approach for biobjective integer programs under quasiconvex preference functions Ozturk, Diclehan Tezcaner; Köksalan, Mustafa Murat (2016-09-01) We develop an interactive algorithm for biobjective integer programs that finds the most preferred solution of a decision maker whose preferences are consistent with a quasiconvex preference function to be minimized. During the algorithm, preference information is elicited from the decision maker. Based on this preference information and the properties of the underlying quasiconvex preference function, the algorithm reduces the search region and converges to the most preferred solution progressively. Findin...
An interactive evolutionary metaheuristic for multiobjective combinatorial optimization Phelps, S; Köksalan, Mustafa Murat (2003-12-01) We propose an evolutionary metaheuristic for multiobjective combinatorial optimization problems that interacts with the decision maker (DM) to guide the search effort toward his or her preferred solutions. Solutions are presented to the DM, whose pairwise comparisons are then used to estimate the desirability or fitness of newly generated solutions. The evolutionary algorithm comprising the skeleton of the metaheuristic makes use of selection strategies specifically designed to address the multiobjective na...
An interactive ranking-based multi-criteria choice algorithm with filtering: Applications to university selection Karakaya, Gülşah (Orta Doğu Teknik Üniversitesi (Ankara, Turkey), 2019-6) In this study, we develop an interactive algorithm to converge to the most preferred alternative of a decision maker (DM) among a set of discrete alternatives. The algorithm presents a limited number of alternatives to the DM and collects preference ranking of them iteratively. The preferences are modeled by a flexible and realistic preference function. To improve the performance, the alternatives presented are determined by a filtering method. We compare our algorithm with benchmark algorithms on nume...
An interactive genetic algorithm applied to the multiobjective knapsack problem Pamuk, S; Köksalan, Mustafa Murat (2001-01-01) Multiobjective combinatorial problems are commonly encountered in practice and would benefit from the development of metaheuristics where the search effort is interactively guided towards the solutions favored by the decision maker. The present study introduces such an Interactive Genetic Algorithm designed for a general multiobjective combinatorial framework and discusses its behavior in simulations on the Multiobjective Knapsack Problem. The evolution strategies being employed reflect the multiobjective n...
An interactive approximation algorithm for multi-objective integer programs Lokman, Banu; Korhonen, Pekka J.; Wallenius, Jyrki (2018-08-01) 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 th...

Citation Formats

E. Karasakal, “An Interactive partitioning approach for multiobjective decision making under a general monotone utility function,” INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, pp. 969–997, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/49099.