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An Improved Genetic Algorithm with Average-bound Crossover and Wavelet Mutation Operations

S. H. Ling, F. H. F. Leung
2006 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Recently, different crossover operations for RCGA have been proposed to improve the efficiency of the algorithm.  ...  This paper presents a real-coded genetic algorithm (RCGA) with new genetic operations (crossover and mutation). They are called the average-bound crossover (ABX) and wavelet mutation (WM).  ...  CONCLUSION An RCGA with improved genetic operations (average-bound crossover and wavelet mutation) has been presented.  ... 
doi:10.1007/s00500-006-0049-7 fatcat:3hy7lbyn4ncnjkzr5ck3yhtrfu

An improved adaptive genetic algorithm

Shifen Han, Li Xiao, S. Zhao
2022 SHS Web of Conferences  
Based on the specific running steps of genetic algorithm, aiming at the shortcomings of genetic algorithm, an improved adaptive genetic algorithm is proposed.  ...  Finally, an example is used for simulation. The simulation results show that the improved algorithm has certain advantages.  ...  This project is supported by the guiding project of the scientific research plan of Hubei Provincial Department of education in 2018, Project Name: Research on production scheduling problem based on Intelligent  ... 
doi:10.1051/shsconf/202214001044 fatcat:5bk34e76rja2jjhswgdqyzrjyy

An Improved Genetic Algorithm for Solving the RGV Shop Scheduling Problem

Hao Fan, Xiaoyan Yu, De-qin Shu, Wei-hong Guan, Zhong-hao Guo, Shuo Feng
2019 Journal of Physics, Conference Series  
In this paper, the characteristics of the RGV job scheduling under the condition of different processes with or without faults are analysed and an improved genetic algorithm is proposed.  ...  And the time efficiency of the improved algorithm is also better than the traditional genetic algorithm.  ...  Innovation Fund Project of Shandong Agricultural University (23659).  ... 
doi:10.1088/1742-6596/1314/1/012133 fatcat:zboeapwpgzew3njqtsee5jecc4

Research and Applications of Shop Scheduling Based on Genetic Algorithms

Hang ZHAO, Fansen KONG
2016 Brazilian Archives of Biology and Technology  
improved cyclic search genetic algorithm is put forward, and chromosome coding method and corresponding operation are given.The operation has the nature of inheriting the optimal individual ofthe previous  ...  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  ...  Before crossover operation, this figure set an initial value so that the genetic algorithm will not in an infinite loop forever.  ... 
doi:10.1590/1678-4324-2016160545 fatcat:flt6movwyraxtc4s44cb4y2z3e

Boundary Evolution Algorithm for SAT-NP [article]

Zhaoyang Ai, Chaodong Fan, Yingjie Zhang, Huigui Rong, Ze'an Tian, Haibing Fu
2018 arXiv   pre-print
Though more extensive comparisons are to be made on more algorithms, the consideration of the boundary elasticity of hierarchical genetic algorithm is an implication of evolutionary algorithm.  ...  A boundary evolution Algorithm (BEA) is proposed by simultaneously taking into account the bottom and the high-level crossover and mutation, ie., the boundary of the hierarchical genetic algorithm.  ...  Design of improved Operators Crossover and Mutation operators based on annealing The traditional hierarchical genetic algorithm often conducts classic algorithm at the bottom.  ... 
arXiv:1903.01894v1 fatcat:t76ktwf3jzc6xnpl5ifsnihioi

Research on Flexible Job Shop Scheduling Problem Based on Improved Genetic Algorithm

Jing-Cao CAI, Lei WANG, Yi-Peng XING
2017 DEStech Transactions on Engineering and Technology Research  
An improved algorithm is proposed based on a basic genetic algorithm to enhance solution quality for solving FJSP in this paper.  ...  The improved algorithm is tested on an instance of 10 jobs and 10 machines for FJSP. The computational results indicate that the proposed improved algorithm is effective for solving FJSP.  ...  Acknowledgement This research was financially supported by the National Natural Science Foundation of China (Grant No.51305001), Key Support Projects for Outstanding Young Talents of Anhui Province Universities  ... 
doi:10.12783/dtetr/mdm2016/4877 fatcat:vgsxingwc5cfpeedz422fd445y

Path Planning of Mobile Robot Based on an Improved Genetic Algorithm

Zhang Yi, Dai En-can, Ren Tong-hui
2016 DEStech Transactions on Engineering and Technology Research  
In the design of genetic operators, many operations such as crossover and mutation are redefined to avoid getting into the local optimum.  ...  Aimed for the problems in traditional genetic algorithm of low search efficiency and easily falling into the local optimal solution, an improved genetic algorithm is proposed in this paper.  ...  Path Planning Based on Improved Genetic Algorithm The main purpose of this paper is to put forward an improved genetic algorithm to solve the problem of path planning for the mobile robot.  ... 
doi:10.12783/dtetr/icmite20162016/4633 fatcat:vzhkg6rpmze6rg6idaznqizuxy

An Improved Evolutionary Algorithm with New Genetic Operation for Optimization Problem

Wang Jiekai, Hu Ruikai, Wang Chao
2014 TELKOMNIKA Indonesian Journal of Electrical Engineering  
In order to control genetic operations in an effective range, the new algorithm regulate both of the crossover probability and mutation probability with the iteration process.  ...  An improved evolutionary algorithm (SCAGA) is proposed in this paper for solving optimization problem.  ...  To reduce the blindness of genetic operations, an improved adaptive genetic algorithm is proposed in this paper.  ... 
doi:10.11591/telkomnika.v12i4.4785 fatcat:7uv4fsriprh77orxlu7rgog2fu


Yu Xiao
2022 Revista Brasileira de Medicina do Esporte  
Results: The algorithm improvement was obtained after analyzing the operation process and structuring of the traditional genetic algorithm; the mathematical model application revealed improvement in the  ...  A genetic algorithm was proposed to adjust the crossover probability and dynamic mutation according to fitness, aiming to solve the problem of dynamic changes.  ...  Therefore, the adaptive genetic algorithm is an important mathematical model to improve the algorithm.  ... 
doi:10.1590/1517-8692202228052021_0537 fatcat:lq5gw4a2vnenjer22ac2eaxsli

Multi-AGV path planning with double-path constraints by using an improved genetic algorithm

Zengliang Han, Dongqing Wang, Feng Liu, Zhiyong Zhao, Xiaosong Hu
2017 PLoS ONE  
double-path constraints by using an improved genetic algorithm.  ...  improved genetic algorithm.  ...  Section 3 investigates an improved genetic algorithm with double-path constraints by using the three-exchange crossover heuristic operators.  ... 
doi:10.1371/journal.pone.0181747 pmid:28746355 pmcid:PMC5528885 fatcat:kzkbla7cz5a3fcdphho4n44pt4

The Operator of Genetic Algorithms to Improve its Properties

Aijun Li
2010 Modern Applied Science  
Based on the traditional genetic algorithm, proposed an improved adaptive genetic algorithm, the experimental results show that the improved adaptive genetic algorithm results than standard genetic algorithm  ...  much better and effective to improve the convergence of genetic algorithm optimization of speed and efficiency.  ...  Improved Adaptive Genetic Algorithm Constraints in the genetic algorithm runs through the genetic operations has always been, this will certainly affect the efficiency of operations.  ... 
doi:10.5539/mas.v4n3p60 fatcat:kg26glvi7newrkv5boyacyi6za

Cloud Task Scheduling Algorithm based on Improved Genetic Algorithm

Hu Yao
2017 International Journal of Performability Engineering  
In this paper, the "three-stage selection method" and the genetic strategy of "totaldivision-total" are put forward to improve genetic algorithm.  ...  (IGA) is better than the simple genetic algorithm on completion time, and it is an effective task scheduling algorithm in cloud computing environment.  ...  In simple genetic algorithms, crossover operation does not take into account the similarity of two individual crossover regions; if the gene similarity of crossover region is too large, crossover operation  ... 
doi:10.23940/ijpe.17.07.p9.10701076 fatcat:wags2idvnfgwhibygwsy4jncve

An improved adaptive genetic algorithm

Song Xudong, Xiao Yunlong
2012 2012 First National Conference for Engineering Sciences (FNCES 2012)  
The high fitness individuals was used to perform decimal coding to improve the search rate based on original adaptive genetic algorithm, as well as the criteria of poor individuals about elitist strategy  ...  In this paper, we proposed a new adaptive genetic algorithm based hybrid coding and elitist strategy.  ...  IMPROVED ADAPTIVE GENETIC ALGORITHM A. The improvement of the algorithm To improve the operating efficiency of the genetic algorithm, we made some improvements to the algorithm.  ... 
doi:10.1109/nces.2012.6543564 fatcat:toj3ulkrnfdb7gy4ukzz66gbmy

Improved Real Coded Genetic Algorithm and Its Simulation

Jianmin Zhu, Donger Zhou, Fucai Li, Tingting Fu
2014 Journal of Software  
generating, overall process of algorithm and the mutation operator, then puts forward an improved real coded genetic algorithm.  ...  This improved algorithm combines the series operation and parallel operation of the three basic operators (selection, crossover and mutation), presents new methods of uniform generating initial population  ...  ALGORITHM STEPS The improved real coded genetic algorithm proposed in this paper combines the parallel operation and the series operation of three basic operators (selection operator, crossover operator  ... 
doi:10.4304/jsw.9.2.389-397 fatcat:ysbgclrc3zc55dynrrh7zkfwcy

Research on Resource Scheduling of Cloud Computing Based on Improved Genetic Algorithm

Juanzhi Zhang, Fuli Xiong, Zhongxing Duan
2020 Journal of Electronic Research and Application  
On the technology of the conventional genetic algorithm, an adaptive transformation operator is designed to improve the crossover and mutation of the genetic algorithm.  ...  The experimental results show that the improved genetic algorithm can significantly reduce the total completion time of the task, and has good convergence and global optimization ability.  ...  As shown in Figure 3 , the crossover probability, mutation probability value, crossover operator and mutation operator of genetic algorithm are adjusted adaptively.  ... 
doi:10.26689/jera.v4i2.1156 fatcat:g7lu3wtogvgajdnxhv2bjzrziy
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