Developing an Adaptation Process for Real-Coded Genetic Algorithms

Saraçoğlu R., Kazankaya A. F.

COMPUTER SYSTEMS SCIENCE AND ENGINEERING, cilt.35, sa.1, ss.13-19, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 35 Sayı: 1
  • Basım Tarihi: 2020
  • Dergi Adı: COMPUTER SYSTEMS SCIENCE AND ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.13-19
  • Anahtar Kelimeler: Adaptive algorithms, Algorithm design and analysis, Genetic algorithms, Value coding genetic algorithms, OPTIMIZATION, CROSSOVER, PROBABILITIES, FLEXIBILITY, OPERATORS, EVOLUTION, MUTATION
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

The genetic algorithm (GA) is a metaheuristic method which simulates the life cycle and the survival of the fittest in the nature for solving optimization problems. This study aimed to develop enhanced operation by modifying the current GA. This development process includes an adaptation method that contains certain developments and adds a new process to the classic algorithm. Individuals of a population will be trialed to adapt to the current solution of the problem by taking them separately for each generation. With this adaptation method, it is more likely to get better results in a shorter time. Experimental results show that this new process accelerated the algorithm and a certain solution has been reached in fewer generations. In addition, better solutions were achieved, especially for a certain number of generations.