Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A method for chromosome handling of r-permutations of n-element set in genetic algorithms
Date
1997-04-16
Author
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
193
views
0
downloads
Cite This
Combinatorial optimisation problems are in the domain of Genetic Algorithms (GA) interest. Unfortunately ordinary crossover and mutation operators cause problems for chromosome representations of permutations and some types of combinations. This is so because offsprings generated by means of the ordinary operators are of a great possibility no more valid chromosomes. A variety of methods and new operators that handle that sort of obscenities are introduced throughout the literature. A new method for representing r-permutations of n-elements as GA chromosomes has been introduced. In contrast to the conventional ones this proposed representation is not handicapped under crossover and mutation. The proposed method is used in various scheduling and timetabling GA applications problems and is observed to perform extremely well.
Subject Keywords
Engines
,
Springs
,
Optimization methods
,
Genetic mutations
,
Encoding
,
Genetic algorithms
,
Biological cells
URI
https://hdl.handle.net/11511/35920
DOI
https://doi.org/10.1109/icec.1997.592268
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
A robust Island Parallel Genetic Algorithm for the Quadratic Assignment Problem
Tosun, Umut; Dokeroglu, Tansel; Coşar, Ahmet (2013-07-01)
The Quadratic Assignment Problem (QAP) is a difficult and important problem studied in the domain of combinatorial optimisation. It is possible to solve QAP instances with 10--20 facilities using exhaustive parallel algorithms within a few days on a cluster machine. However, large QAP instances with more than 100 facilities are not solvable using exhaustive techniques. We have explored a variety of Genetic Algorithm crossover operators for this problem and verified its performance experimentally using well-...
Evaluation of crossover techniques in genetic algorithm based optimum structural design
Hasançebi, Oğuzhan (2000-11-01)
Crossover is one of the three basic operators in any genetic algorithm (GA). Several crossover techniques have been proposed and their relative merits are currently under investigation. This paper starts with a brief discussion of the working scheme of the GAs and the crossover techniques commonly used in previous GA applications. Next, these techniques are tested on two truss size optimization problems, and are evaluated with respect to exploration and exploitation aspects of the search process. Finally, t...
On the use of genetic algorithms for synthesis of signal temporal logic formulas
Aydin, Sertac Kagan; Aydın Göl, Ebru (2018-07-09)
In this work, we studied use of genetic algorithms to synthesize Signal Temporal Logic formulas from a labeled data set. In the synthesis problem, the goal is to generate the best STL formula representing the labeled signals in the set. To use genetic algoritms in this domain, the basic genetic algoritm processes are defined for STL formulas. The developed synthesis method produces a formula from the data set efficiently in a fully automated way. In particular, the proposed approach does not require an expe...
Optimization of the array geometry for direction finding
Özaydın, Seval; Koç, Seyit Sencer; Tanık, Yalçın; Department of Electrical and Electronics Engineering (2003)
In this thesis, optimization of the geometry of non-uniform arrays for direction finding yielding unambiguous results is studied. A measure of similarity between the array response vectors is defined. In this measure, the effects of antenna array geometry, source placements and antenna gains are included as variable parameters. Then, assuming that the antenna gains are known and constant, constraints on the similarity function are developed and described to result in unambiguous configurations and maximum r...
A New Representation of Elements of Binary Fields with Subquadratic Space Complexity Multiplication of Polynomials
Özbudak, Ferruh; Cenk, Murat (2013-10-01)
In this paper, Hermite polynomial representation is proposed as an alternative way to represent finite fields of characteristic two. We show that multiplication in Hermite polynomial representation can be achieved with subquadratic space complexity. This representation enables us to find binomial or trinomial irreducible polynomials which allows us faster modular reduction over binary fields when there is no desirable such low weight irreducible polynomial in other representations. We then show that the pro...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
G. Üçoluk, “A method for chromosome handling of r-permutations of n-element set in genetic algorithms,” 1997, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35920.