Generating a Representative Subset of the Nondominated Frontier in Multiple Criteria Decision Making

In this paper, we address the problem of generating a discrete representation of the nondominated frontier in multiple objective linear problems. We find a surface that approximates the shape of the nondominated frontier. Utilizing the surface, we generate a set of discrete points that is representative of the frontier. Our experience on randomly generated problems demonstrates that the approach performs well in terms of both the quality of the representation and the computation time.


Generating representative nondominated point subsets in multi-objective integer programs
Ceyhan, Gökhan; Köksalan, Murat; Lokman, Banu; Department of Industrial Engineering (2014)
In this thesis, we study generating a subset of all nondominated points of multi-objective integer programs in order to represent the nondominated frontier. Our motivation is based on the fact that generating all nondominated points of a multi-objective integer program is neither practical nor useful. The computational burden could be prohibitive and the resulting set could be huge. Instead of finding all nondominated points, we develop algorithms to generate a small representative subset of nondominated po...
Efficient Three-Layer Iterative Solutions of Electromagnetic Problems Using the Multilevel Fast Multipole Algorithm
Onol, Can; Ucuncu, Arif; Ergül, Özgür Salih (2017-05-19)
We present a three-layer iterative algorithm for fast and efficient solutions of electromagnetic problems formulated with surface integral equations. The strategy is based on nested iterative solutions employing the multilevel fast multipole algorithm and its approximate forms. We show that the three-layer mechanism significantly reduces solution times, while it requires no additional memory as opposed to algebraic preconditioners. Numerical examples involving three-dimensional scattering problems are prese...
Improved rule discovery performance on uncertainty
Tolun, MR; Sever, H (1998-01-01)
In this paper we describe the improved version of a novel rule induction algorithm, namely ILA. We first outline the basic algorithm, and then present how the algorithm is enhanced using the new evaluation metric that handles uncertainty in a given data set. In addition to having a faster induction than the original one, we believe that our contribution comes into picture with a new metric that allows users to define their preferences through a penalty factor. We use this penalty factor to tackle with over-...
Solving the Forward Kinematics of the 3RPR Planar Parallel Manipulator using a Hybrid Meta-Heuristic Paradigm
Chandra, Rohitash; Zhang, Mengjie; Rolland, Luc (2009-12-18)
The forward kinematic of the 3-RPR parallel manipulator is solved using a hybrid meta-heuristic technique where the simulated annealing algorithm replaces the mutation operator in a genetic algorithm. The results from the hybrid meta-heuristic approach is compared with the standard simulated annealing and genetic algorithm. The results show that the simulated annealing algorithm outperforms genetic algorithm in terms of computation time and overall accuracy of the solution. The hybrid meta-heuristic search ...
Constructing sequences with high nonlinear complexity using the Weierstrass semigroup of a pair of distinct points of a Hermitian curve
Geil, Olav; Özbudak, Ferruh; Ruano, Diego (Springer Science and Business Media LLC, 2019-06-01)
Using the Weierstrass semigroup of a pair of distinct points of a Hermitian curve over a finite field, we construct sequences with improved high nonlinear complexity. In particular we improve the bound obtained in Niederreiter and Xing (IEEE Trans Inf Theory 60(10):6696-6701, 2014, Theorem3) considerably and the bound in Niederreiter and Xing (2014, Theorem4) for some parameters.
Citation Formats
E. Karasakal, “Generating a Representative Subset of the Nondominated Frontier in Multiple Criteria Decision Making,” OPERATIONS RESEARCH, pp. 187–199, 2009, Accessed: 00, 2020. [Online]. Available: