New crossover operators for Real Coded Genetic Algorithm (RCGA)

被引:0
作者
Singh, Gurjot [1 ]
Gupta, Neeraj [2 ]
Khosravy, Mahdi [2 ]
机构
[1] Indian Inst Technol, Jodhpur, Rajasthan, India
[2] Univ Informat Sci & Technol, Ohrid, Macedonia
来源
2015 INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATICS AND BIOMEDICAL SCIENCES (ICIIBMS) | 2015年
关键词
Genetic algorithm; traveling salesman problem; crossover; Simulated annealing;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper aims at achieving global optimal solution of complex problems, such as traveling salesman problem (TSP), using extended version of real coded genetic algorithms (RCGA). Since genetic algorithm (GA) consists of several genetic operators, namely selection procedure, crossover, and mutation operators, that offers the choice to be modified in order to improve the performance for particular implementation, we propose three new crossover techniques for Real Coded Genetic Algorithms, which will improve the quality of solution as well as the rate of convergence to the optimum solution. Methods proposed for crossover operators are inspired by asexual reproduction commonly observed in nature. In this regard, new crossover techniques proposed incorporates the concept of Boltzmann's distribution (BD) for escaping local optima by allowing hill-climbing moves and Metropolis Algorithm (MPA), where, survival of offspring is tested before transit to new generation. Finally, these three methods are compared on various aspects like rate of convergence and quality of final solution among each other and against other randomized algorithms.
引用
收藏
页码:135 / 140
页数:6
相关论文
共 50 条
[41]   Playing the Original Game Boy Tetris Using a Real Coded Genetic Algorithm [J].
da Silva, Renan Samuel ;
Parpinelli, Rafael Stubs .
2017 6TH BRAZILIAN CONFERENCE ON INTELLIGENT SYSTEMS (BRACIS), 2017, :282-287
[42]   Real-coded Genetic Algorithm and Application in the Automatic Composing the Test Paper [J].
Wang Yu-Fen ;
Guo Xiao-Juan .
2009 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL 1, PROCEEDINGS, 2009, :399-402
[43]   A genetic algorithm with conditional crossover and mutation operators and its application to combinatorial optimization problems [J].
Wang, Rong-Long ;
Fukuta, Shinichi ;
Wang, Jia-Hai ;
Okazaki, Kozo .
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2007, E90A (01) :287-294
[44]   An Improved Real-Coded Genetic Algorithm for the Beam Forming of Spaceborne SAR [J].
Shi, Li ;
Deng, Yun-kai ;
Sun, Hui-feng ;
Wang, Robert ;
Ai, Jia-qiu ;
Yan, He .
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2012, 60 (06) :3034-3040
[45]   Generation of JPEG Quantization Table using Real Coded Quantum Genetic Algorithm [J].
Kumar, B. Vinoth ;
Karpagam, G. R. ;
Naresh, S. P. .
2016 INTERNATIONAL CONFERENCE ON COMMUNICATION AND SIGNAL PROCESSING (ICCSP), VOL. 1, 2016, :1705-1709
[46]   Sensor/actuators placement on civil structures using a real coded genetic algorithm [J].
Richardson, A ;
Abdullah, MM .
SMART STRUCTURES AND MATERIALS 2002: SMART SYSTEMS FOR BRIDGES, STRUCTURES, AND HIGHWAYS, 2002, 4696 :244-255
[47]   A real-coded genetic algorithm considering gestalt principles to building displacement [J].
Sun, Yageng ;
Guo, Qingsheng ;
Liu, Yuangang ;
Lv, Xiuqin ;
Zheng, Chunyan .
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2015, 40 (02) :269-273
[48]   FPGA Implementation of Crossover Module of Genetic Algorithm [J].
Attarmoghaddam, Narges ;
Li, Kin Fun ;
Kanan, Awos .
INFORMATION, 2019, 10 (06)
[49]   Real-Coded Genetic Algorithm for Solving Generalized Polynomial Programming Problems [J].
Wu, Jui-Yu ;
Chung, Yun-Kung .
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2007, 11 (04) :358-364
[50]   Hybrid Real-Coded Genetic Algorithm with Quasi-Simplex Technique [J].
Zhang, Guoli ;
Lu, Haiyan .
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2006, 6 (10) :246-255