Banu Lokman

E-mail
lbanu@metu.edu.tr
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Scopus Author ID
Finding the Nondominated Set and Efficient Integer Vectors for a Class of Three-Objective Mixed-Integer Linear Programs
Ceyhan, Gokhan; Köksalan, Mustafa Murat; Lokman, Banu (2023-03-01)
We consider a class of three-objective mixed-integer linear programs (MILPs) where at least one of the objective functions takes only discrete values. These problems commonly occur in MILPs where one or more of the three o...
Extensions for Benders cuts and new valid inequalities for solving the European day-ahead electricity market clearing problem efficiently
Ceyhan, Gökhan; Köksalan, Mustafa Murat; Lokman, Banu (2022-07-16)
© 2021 Elsevier B.V.We study the day-ahead electricity market clearing problem under the prevailing market design in the European electricity markets. We revisit the Benders decomposition algorithm that has been used to so...
Representing the nondominated set in multi-objective mixed-integer programs
Doğan, Ilgın; Lokman, Banu; Köksalan, Murat (2021-01-01)
In this paper, we consider generating a representative subset of nondominated points at a prespecified precision in multi-objective mixed-integer programs (MOMIPs). The number of nondominated points grows exponentially wit...
Distribution based representative sets for multi-objective integer programs
Ozarik, Sami Serkan; Lokman, Banu; Koksalan, Murat (2020-07-16)
We study and exploit the characteristics of the nondominated sets of Multi-objective Integer Programs (MOIPs). We introduce a density measure and search for common properties of the distributions of nondominated points for...
Finding a representative nondominated set for multi-objective mixed integer programs
Ceyhan, Gokhan; Koksalan, Murat; Lokman, Banu (2019-01-01)
In this paper, we develop algorithms to find small representative sets of nondominated points that are well spread over the nondominated frontiers for multi-objective mixed integer programs. We evaluate the quality of repr...
Identifying preferred solutions in multiobjective combinatorial optimization problems
Lokman, Banu (2019-01-01)
We develop an evolutionary algorithm for multiobjective combinatorial optimization problems. The algorithm aims at converging the preferred solutions of a decision-maker. We test the performance of the algorithm on the mul...
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 consiste...
Approximating the Nondominated Frontiers of Multi-Objective Combinatorial Optimization Problems
Koksalan, Murat; Lokman, Banu (2009-03-01)
Finding, all nondominated vectors for multi-objective combinatorial optimization (MOCO) problems is computationally very hard in general. We approximate the nondominated Frontiers of MOCO problems by fitting smooth hypersu...
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