Design and usage of a new benchmark problem for genetic programming

Date

2003-01-01

Author

KORKMAZ, EMİN ERKAN
Üçoluk, Göktürk

Metadata

Show full item record

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

Item Usage Stats

91
views

0
downloads

Not so many benchmark problems have been proposed in the area of Genetic Programming (GP). In this study, a new artificial benchmark problem is designed for GP. The different parameters that can be used to tune the difficulty of the problem are analyzed. Also, the initial experimental results obtained on different instances of the problem are presented.

Subject Keywords

Benchmark problem, Computer Engineer Department, Terminal element, Full binary tree, Real world domain

URI

https://hdl.handle.net/11511/53809

Journal

COMPUTER AND INFORMATION SCIENCES - ISCIS 2003

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Application of genetic algorithms to geometry optimization of microclusters: A comparative study of empirical potential energy functions for silicon Erkoc, S; Leblebicioğlu, Mehmet Kemal; Halıcı, Uğur (Informa UK Limited, 2003-01-01) Evolutionary computation techniques (in particular, genetic algorithms) have been applied to optimize the structure of microclusters. Various empirical potential energy functions have been used to describe the interactions among the atoms in the clusters. A comparative study of silicon microclusters has been performed.
An evaluation of a novel approach for clustering genes with dissimilar replicates Cinar, Ozan; İyigün, Cem; İlk Dağ, Özlem (Informa UK Limited, 2020-12-01) Clustering the genes is a step in microarray studies which demands several considerations. First, the expression levels can be collected as time-series which should be accounted for appropriately. Furthermore, genes may behave differently in different biological replicates due to their genetic backgrounds. Highlighting such genes may deepen the study; however, it introduces further complexities for clustering. The third concern stems from the existence of a large amount of constant genes which demands a hea...
Impact of crossover and decision variable coding forms on the performance of genetic algorithm optimization a case study on pump and treat remediation design GÜNGÖR DEMİRCİ, Gamze; Aksoy, Ayşegül (2008-05-23) Genetic algorithms (GAs) are robust methods applied especially for complex optimization problems. However, selection of some GA parameters may play a vital role on the efficacy of the method. This study investigates the impacts of crossover type and form of coding on the performance of optimization by genetic algorithms. For this purpose, two pump-and-treat remediation design problems were considered with different levels of complexity determined by the number of decision variables. The efficiencies of GA f...
Multiploid genetic algorithms for multi-objective turbine blade aerodynamic optimization Öksüz, Özhan; Akmandor, İbrahim Sinan; Department of Aerospace Engineering (2007) To decrease the computational cost of genetic algorithm optimizations, surrogate models are used during optimization. Online update of surrogate models and repeated exchange of surrogate models with exact model during genetic optimization converts static optimization problems to dynamic ones. However, genetic algorithms fail to converge to the global optimum in dynamic optimization problems. To address these problems, a multiploid genetic algorithm optimization method is proposed. Multi-fidelity surrogate m...
A genetic algorithm for TSP with backhauls based on conventional heuristics Önder, İlter; Özdemirel, Nur Evin; Department of Information Systems (2007) A genetic algorithm using conventional heuristics as operators is considered in this study for the traveling salesman problem with backhauls (TSPB). Properties of a crossover operator (Nearest Neighbor Crossover, NNX) based on the nearest neighbor heuristic and the idea of using more than two parents are investigated in a series of experiments. Different parent selection and replacement strategies and generation of multiple children are tried as well. Conventional improvement heuristics are also used as mut...

Citation Formats

E. E. KORKMAZ and G. Üçoluk, “Design and usage of a new benchmark problem for genetic programming,” COMPUTER AND INFORMATION SCIENCES - ISCIS 2003, pp. 561–567, 2003, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53809.