Genetic algorithm solution of the TSP avoiding special crossover and mutation

Download

index.pdf

Date

2002-01-01

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

143
views

0
downloads

Ordinary representations of permutations in Genetic Algorithms (GA) is handicapped with producing offspring which are not permutations at all. The conventional solution for crossover and mutation operations of permutations is to device 'special' operators. Unfortunately these operators suffer from violating the nature of crossover. Namely, considering the gene positions on the chromosome, these methods do not allow n-point crossover techniques which are known to favour building-block formations. In this work, an inversion sequence is proposed as the representation of a permutation. This sequence allows repetitive values and hence is robust under ordinary (n-point) crossover. There is a one-to-one mapping from ordinary permutation representation to the inversion sequence representation.

Subject Keywords

Theoretical Computer Science, Computational Theory and Mathematics, Software, Artificial Intelligence

URI

https://hdl.handle.net/11511/49201

Journal

INTELLIGENT AUTOMATION AND SOFT COMPUTING

DOI

https://doi.org/10.1080/10798587.2000.10642829

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

A Favorable Weight-Based Evolutionary Algorithm for Multiple Criteria Problems SOYLU, Banu; Köksalan, Mustafa Murat (Institute of Electrical and Electronics Engineers (IEEE), 2010-04-01) In this paper, we present a favorable weight-based evolutionary algorithm for multiple criteria problems. The algorithm tries to both approximate the Pareto frontier and evenly distribute the solutions over the frontier. These two goals are common for many multiobjective evolutionary algorithms. To achieve these goals in our algorithm, each member selects its own weights for a weighted Tchebycheff distance function to define its fitness score. The fitness scores favor solutions that are closer to the Pareto...
Modified Redundant Representation for Designing Arithmetic Circuits with Small Complexity AKLEYLEK, SEDAT; Özbudak, Ferruh (Institute of Electrical and Electronics Engineers (IEEE), 2012-03-01) We give a modified redundant representation for designing arithmetic circuits with small complexity. Using our modified redundant representation, we improve many of the complexity values significantly. Our method works for any finite field. We also give some applications in cryptography.
Learning customized and optimized lists of rules with mathematical programming Rudin, Cynthia; Ertekin Bolelli, Şeyda (Springer Science and Business Media LLC, 2018-12-01) We introduce a mathematical programming approach to building rule lists, which are a type of interpretable, nonlinear, and logical machine learning classifier involving IF-THEN rules. Unlike traditional decision tree algorithms like CART and C5.0, this method does not use greedy splitting and pruning. Instead, it aims to fully optimize a combination of accuracy and sparsity, obeying user-defined constraints. This method is useful for producing non-black-box predictive models, and has the benefit of a clear ...
Improved probabilistic decoding of interleaved Reed-Solomon codes and folded Hermitian codes Özbudak, Ferruh (Elsevier BV, 2014-02-06) Probabilistic simultaneous polynomial reconstruction algorithm of Bleichenbacher, Kiayias, and Yung is extended to the polynomials whose degrees are allowed to be distinct. Specifically, for a finite field F, positive integers n, r, t and distinct elements z(1), z(2), ... , z(n) is an element of F, we present a probabilistic algorithm which can recover polynomials p(1), p(2), p(r) is an element of F[x] of degree less than k(1), k(2), ... , k(r) respectively for a given instance < y(i), (1, ... ,) y(i,r)>(n)...
Strongly regular graphs arising from non-weakly regular bent functions Özbudak, Ferruh (Springer Science and Business Media LLC, 2019-11-01) In this paper, we study two special subsets of a finite field of odd characteristics associated with non-weakly regular bent functions. We show that those subsets associated to non-weakly regular even bent functions in the GMMF class (see cesmelioglu et al. Finite Fields Appl. 24, 105-117 2013) are never partial difference sets (PDSs), and are PDSs if and only if they are trivial subsets. Moreover, we analyze the two known sporadic examples of non-weakly regular ternary bent functions given in Helleseth and...

Citation Formats

G. Üçoluk, “Genetic algorithm solution of the TSP avoiding special crossover and mutation,” INTELLIGENT AUTOMATION AND SOFT COMPUTING, pp. 265–272, 2002, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/49201.