# Empirical evaluation of changing crossover operators to solve function optimization problems

@article{Takahashi2016EmpiricalEO, title={Empirical evaluation of changing crossover operators to solve function optimization problems}, author={R. Takahashi}, journal={2016 IEEE Symposium Series on Computational Intelligence (SSCI)}, year={2016}, pages={1-10} }

In this paper, the effectiveness of methodologies for changing crossover operators (CXOs) to solve function optimization problems (FOP) are empirically validated in order to solve the problems of premature convergence in genetic algorithms. CXOs are methods of finding solutions for combinatorial optimization problems through genetic algorithms (GAs) while maintaining the balance of satisfying the contrary requisites for GAs: to sustain the diversity of the population and to improve the… Expand

#### Figures, Tables, and Topics from this paper

#### 4 Citations

Ant Colony Optimization with Stepwise Localization of the Discrete Search Space to Solve Function Optimization Problems

- Computer Science
- 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)
- 2017

This work examined methods that search for solutions in the real space Rn by approximating them using discrete values (binary data) and proposed improved-EAS, an improvement on the elitist ant system, which is capable of stepwise localization of the search space. Expand

Experimental Evaluation of ACO for Continuous Domains to Solve Function Optimization Problems

- Mathematics, Computer Science
- ANTS Conference
- 2018

Experiments show that a new Ant Colony Optimization to solve function optimization problems (FOP) can keep the balance between accuracy and efficiency to search for optimum solutions, and that it can reduce the population size of \(\text {ACO}_\text {R}\), which is a preceding ACO based on real search space. Expand

A Multi-granularity Genetic Algorithm

- Computer Science
- 2019 IEEE International Conference on Big Knowledge (ICBK)
- 2019

An improved genetic algorithm that divides the feasible region into multiple granularities and adopts a multi-granularity space strategy based on a random tree, which accelerates the searching speed of the algorithm in the multi- granular space. Expand

Beam Shape Optimization Method for Low Outage Beamforming Training with Limited Number of Beams

- Computer Science
- 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications
- 2020

The results of computer simulations demonstrate that better outage performance can be achieved by beams optimized by the proposed method when compared with a method to optimize each beam separately based on a given beam width. Expand

#### References

SHOWING 1-10 OF 37 REFERENCES

Solving the Traveling Salesman Problem through Iterative Extended Changing Crossover Operators

- Computer Science
- 2011 10th International Conference on Machine Learning and Applications and Workshops
- 2011

The diversity of generations is strictly measured by the entropy H in Thermo Dynamical Genetic Algorithm (TDGA) and the validity of i-ECXO is experimentally verified by using medium sized TSP data. Expand

Quantitative evaluation of iterative extended changing crossover operators to solve the traveling salesman problem: Diversity measurement and its application to selection strategies in genetic algorithms

- Mathematics, Computer Science
- 2014 10th International Conference on Natural Computation (ICNC)
- 2014

i-ECXO is a hybrid method to unite Edge Assembly Crossover to Ant Colony Optimization, immune Genetic Algorithm realizes Jerne's network which harmonizes the immune system by making another antibodies work antigens for each antibody, and above three methods are evaluated by using the edges' entropy H in TDGA. Expand

The Frontiers of Real-coded Genetic Algorithms

- Computer Science
- 2009

A generation alternation model called JGG (just generation gap) suited for multi-parental crossovers, and a crossover called REX(φ,n + k) as a generlization of the e-UNDX, where φ and n + k denote some probability distribution and the number of parents respectively. Expand

A genetic solution for the traveling salesman problem by means of a thermodynamical selection rule

- Mathematics, Computer Science
- Proceedings of IEEE International Conference on Evolutionary Computation
- 1996

The authors apply a novel selection rule, the Thermodynamical Genetic Algorithm (TDGA), proposed by N. Mori et al. (1995) to the traveling salesman problem (TSP), and propose an adaptive annealing schedule of the temperature in TDGA. Expand

Verification of thermo-dynamical genetic algorithm to solve the function optimization problem through diversity measurement — Diversity measurement and its application to selection strategies in genetic algorithms

- Mathematics, Computer Science
- 2016 IEEE Congress on Evolutionary Computation (CEC)
- 2016

In this paper, it is experimentally verified that TDGA (Thermo Dynamical Genetic Algorithm) is effective in solving a function optimization problem using Genetic Algorithms, because of its… Expand

An improved binary-real coded genetic algorithm for real parameter optimization

- Computer Science
- 2011 Third World Congress on Nature and Biologically Inspired Computing
- 2011

The quality and time performance of BRGA against the benchmark suite and in comparison with original component algorithms (BGA and RGA) is reported and analyzed and is compared with other Evolutionary Algorithms (EAs) from the literature. Expand

A crossover operator using independent component analysis for real-coded genetic algorithms

- Mathematics
- Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546)
- 2001

For real-coded genetic algorithms, there have been proposed many crossover operators. The blend crossover (BLX-/spl alpha/) proposed by L.J. Eshelman and J.D. Schaffer (1993) shows a good searching… Expand

An evolutionary algorithm for large traveling salesman problems

- Mathematics, Medicine
- IEEE Trans. Syst. Man Cybern. Part B
- 2004

Findings imply that the proposed method can find tours robustly with a fixed small population and a limited family competition length in reasonable time, when used to solve large TSPs. Expand

Multiple solution search based on hybridization of real-coded evolutionary algorithm and quasi-newton method

- Mathematics, Computer Science
- 2007 IEEE Congress on Evolutionary Computation
- 2007

Two hybrid algorithms combining real-coded evolutionary computation algorithms and gradient search methods for multiple-solution search in multimodal optimization problems are proposed and a new evaluation function of solution candidates with gradient is presented and discussed in order to find quasi-optimal solutions. Expand

Empirical review of standard benchmark functions using evolutionary global optimization

- Computer Science, Mathematics
- ArXiv
- 2012

We have employed a recent implementation of genetic algorithms to study a range of standard benchmark functions for global optimization. It turns out that some of them are not very useful as… Expand