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The automatic generation of mutation operators for genetic algorithms

John R. Woodward, Jerry Swan
2012 Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion - GECCO Companion '12  
We automatically generate mutation operators for Genetic Algorithms (GA) and tune them to problem instances drawn from a given problem class.  ...  Iterated local search is used to search the space of mutation operators, and on a test-bed of 7 problem classes we identify machine-designed mutation operators which outperform their human counterparts  ...  Genetic Programming (GP) [4] is a standard method for automatically generating algorithms.  ... 
doi:10.1145/2330784.2330796 dblp:conf/gecco/WoodwardS12 fatcat:amn5x25mrrfvlbut2jzfhuwgbe

The Algorithm for Algorithms: An Evolutionary Algorithm Based on Automatic Designing of Genetic Operators

Dazhi Jiang, Zhun Fan
2015 Mathematical Problems in Engineering  
The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space.  ...  In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions.  ...  Acknowledgments The authors would like to thank the anonymous reviewers for their very detailed and helpful comments that help us to increase the quality of this work.  ... 
doi:10.1155/2015/474805 fatcat:uzgqpw5bejhifndyrtoxsao3e4

Parameter Optimization Design for Automatic Cotton Blending Based on Improved Adaptive Genetic Algorithm

Huaizhong Chen
2018 Journal of Information Hiding and Multimedia Signal Processing  
On the basis of analysis of the standard genetic algorithm shortcomings in the process parameters optimization of mechanized cotton.  ...  a kind of improved adaptive genetic algorithm optimization method.  ...  This work is supported by scientific research funded project of Zhejiang Industry Polytechnic College and scientific research funded project of Science Technology Department of Zhejiang Province (2015C31128  ... 
dblp:journals/jihmsp/Chen18 fatcat:srmv3agyrfgbphhmefutxl2yxq

Software Testing Strategy Approach on Source Code Applying Conditional Coverage Method

Jaya Srivastaval, Twinkle Dwivedi
2015 International Journal of Software Engineering & Applications  
Test case data is generated automatically using genetic algorithm are optimized and outperforms the test cases generated by random testing.  ...  Hence test case generation may be treated as an optimization problem In this paper we have used genetic algorithm to optimize the test case that are generated applying conditional coverage on source code  ...  ACKNOWLEDGMENT We are thankful to the faculty of Computer Science and Engineering, Shri Ramswaroop Memorial University for the motivation and continuous support time to time.  ... 
doi:10.5121/ijsea.2015.6303 fatcat:balwtbsm35hl7ltkqgmhnvmcuu

Review of Genetic Algorithm and Application in Software Testing

Patrick Kwaku, Elias Nii, Wolali Ametepe
2017 International Journal of Computer Applications  
This paper reviews the use of Genetic algorithm to automatically generate test case using the random method.  ...  Software testing consumers a lot of time, effort and money, therefore the focus of testing largely depends on test case generation, execution and evaluation.  ...  Genetic Operators Genetic algorithm uses three main operators which are selection, crossover and mutation.  ... 
doi:10.5120/ijca2017912965 fatcat:2wvsopmycfgabi4t242qeskmlu

Solving the no-wait job-shop problem by using genetic algorithm with automatic adjustment

Wojciech Bożejko, Mariusz Makuchowski
2011 The International Journal of Advanced Manufacturing Technology  
This paper describes a methodology of automatic genetic algorithm parameters adjustment dedicated to a job-shop problem with a no-wait constraint with a makespan criterion.  ...  The numerical results show that in a given problem, the efficiency of an algorithm with auto-tuning is placed at the level of an algorithm steered in a classical way with the best-fit steering parameters  ...  Acknowledgements The work was partially supported by the  ... 
doi:10.1007/s00170-011-3297-3 fatcat:4ajdoh57ofefzhvpkp2hsgghbm

AN IMPROVED GENETIC ALGORITHM FOR TEST DATA GENERATION FOR SIMULINK MODELS

Le Thi My Hanh, Nguyen Thanh Binh, Khuat Thanh Tung
2017 Journal of Computer Science and Cybernetics  
This algorithm involves some modifications of genetic operators and the employment of memory mechanism to enhance its effectiveness.  ...  Although many research works have been done in the field of search-based testing, automatic test data generation based on the mutation analysis method is not straightforward.  ...  A mutation operator for the improved genetic algorithm In addition to the crossover operation, the mutation operator [18] used to maintain genetic diversity from one generation of a population of individuals  ... 
doi:10.15625/1813-9663/33/1/9315 fatcat:zs5z4nbe5nferme22sxwq4rle4

Research and Applications of Shop Scheduling Based on Genetic Algorithms

Hang ZHAO, Fansen KONG
2016 Brazilian Archives of Biology and Technology  
generation and is able to avoid the emergence of local minimum, and cyclic and crossover operation and mutation operation can enhance the diversity of the population and then quickly get the optimal individual  ...  Existing studies have shown that improved genetic algorithm has solved the limitations that existed in the genetic algorithm, the objective function is able to meet customers' needs for shop scheduling  ...  mutation operation Figure 7 Figure 8 78 Figure 7 Convergent curve of genetic algorithm for FT(6X6) Figure 9 - 9 Figure 9 -Compare of Convergent curveCONCLUSIONSo far a lot of genetic algorithms can  ... 
doi:10.1590/1678-4324-2016160545 fatcat:flt6movwyraxtc4s44cb4y2z3e

A Review of Random Test Case Generation using Genetic Algorithm

Deepti Bala Mishra, Saurabh Bilgaiyan, Rajashree Mishra, Arup Abhinna Acharya, Samaresh Mishra
2017 Indian Journal of Science and Technology  
Findings: Genetic Algorithms are successfully used in software testing with increasing number of test case generation and provides a means of an automatic test case generator.  ...  Applications/Improvements: This study gives us a brief idea to implement Genetic Algorithms in software testing for optimum results and also it can be used with the neural networks and fuzzy systems for  ...  The applied a new algorithm called as Genetic-Particle Swarm Mixed Algorithm (GPSMA) to automatically generate software test data.  ... 
doi:10.17485/ijst/2017/v10i30/107654 fatcat:stvw5oweknblnc5ysr4vt3gg4y

A Review of Random Test Case Generation using Genetic Algorithm

Deepti Bala Mishra, Saurabh Bilgaiyan, Rajashree Mishra, Arup Abhinna Acharya, Samaresh Mishra
2017 Indian Journal of Science and Technology  
Findings: Genetic Algorithms are successfully used in software testing with increasing number of test case generation and provides a means of an automatic test case generator.  ...  Applications/Improvements: This study gives us a brief idea to implement Genetic Algorithms in software testing for optimum results and also it can be used with the neural networks and fuzzy systems for  ...  The applied a new algorithm called as Genetic-Particle Swarm Mixed Algorithm (GPSMA) to automatically generate software test data.  ... 
doi:10.17485/ijst/2017/v10i19/107654 fatcat:mosskmlnzfgxlk4mziueurfv34

Smart and Dynamic Time Table Generator

M. D. Boomija
2019 International Journal for Research in Applied Science and Engineering Technology  
In order to reduce this defect we use genetic algorithm to generate a dynamic timetable.  ...  The manual operation of the timetable preparation in college is very monotonous, time consuming and very difficult process.  ...  CONCLUSION As discussed, an evolutionary algorithm, genetics algorithm for time tabling has been proposed. The intention of the algorithm to generate a time-table schedule automatically is satisfied.  ... 
doi:10.22214/ijraset.2019.3205 fatcat:y2xbeopcfvbyhig6dvja6jggny

Electronic Circuit Automatic Design Based on Genetic Algorithms

Xuesong Yan, Wei Li, Yuzhen Zhang, Huihui Zhang, Jianfei Wu
2011 Procedia Engineering  
In this paper, proposed one kind of genetic algorithms which uses in the electronic circuit automatic design and through the experiment proved, this algorithm obtains the circuit structure to surpass the  ...  for the duty change.  ...  B Genetic Operation Crossover Operation: Crossover operation is the main method for the genetic algorithms to generate the new individual.  ... 
doi:10.1016/j.proeng.2011.08.555 fatcat:wwpxdkczmnc35c7wmcyelklwle

T-GEN: A Tabu Search Based Genetic Algorithm for the Automatic Playlist Generation Problem

Sneha Antony, J.N. Jayarajan
2015 Procedia Computer Science  
Genetic algorithm is a promising technique for generating automatically, sequences of music that satisfy arbitrary user criteria.  ...  But this has a disadvantage of selecting clones of the individuals as parents for the next generation.  ...  To apply the genetic operators of selection, crossover and mutation, an initial population is randomly generated.  ... 
doi:10.1016/j.procs.2015.02.038 fatcat:r2cvrqf3s5hgndf7mplnks3e2y

Automatic Timetable Generation using Genetic Algorithm
IJARCCE - Computer and Communication Engineering

Dipesh Mittal, Hiral Doshi, Mohammed Sunasra, Renuka Nagpure
2015 IJARCCE  
By using Genetic algorithm we are able to reduce the time require to generate time table and generate a timetable which is more accurate, precise and free of human errors.  ...  To create timetable it requires lots of time and man power .In our paper we have tried to reduce these difficulties of generating timetable by Genetics Algorithm.  ...  RenukaNagpure, Department of Information Technology, Atharva college of Engineeirng.  ... 
doi:10.17148/ijarcce.2015.4254 fatcat:ka3zz65jvzcwjnw75wytociqvm

Genetic Algorithm for Document Clustering with Simultaneous and Ranked Mutation

K. Premalatha, A.M. Natarajan
2009 Modern Applied Science  
In simultaneous mutation the genetic algorithm concurrently uses several mutation operators in producing the next generation.  ...  In each stage of the genetic process in a problem, may involve aptly different mutation operators for best results.  ...  Initially, the mutation ratios are the same for all operators. After a new generation or several generations, the mutation ratio of each operator is automatically and dynamically adjusted.  ... 
doi:10.5539/mas.v3n2p75 fatcat:e7rc5arxfrfwtpw5iqzbovpueq
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