A New Real-valued Diploid Genetic Algorithm for Optimization in Dynamic Environments
Publish place: 12th Iranian Conference on Intelligent Systems
Publish Year: 1392
نوع سند: مقاله کنفرانسی
زبان: English
View: 1,218
This Paper With 6 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICS12_247
تاریخ نمایه سازی: 11 مرداد 1393
Abstract:
Many real-world problems are dynamic, requiring an optimization algorithm which is able to continuously track a changing optimum over the time. Using a diploidy anddominance is one method to enhance the performance of genetic algorithms in dynamic environment. Diploid genetic algorithm has two chromosomes in each individual. In this paper, for the first time, a real-valued diploid genetic algorithm is proposed. Its new dominance mechanism is basedon a simple function with homogeneous outputs. In addition, a new dominance change mechanism is added to the algorithm.Hence, when environment change occurs, it can increase diversity to respond more quickly to the changes. Other diploid genetic algorithms in literature are discrete and theyhave never been tested by Moving Peak Benchmark (MPB) which is continuous and dynamic. For the first time, theproposed approach is tested by MPB. Results are compared with other diploid genetic algorithms showing that proposed algorithm significantly outperforms previous approaches.
Authors
Amineh Omidpour
Department of electronic, Computer and IT Qazvin Branch, Islamic Azad University Qazvin, Iran
Kamran Alagheband
Department of Mechanical Engineering Shiraz University Shiraz, Iran
Babak Nasiri
Department of electronic, Computer and IT Qazvin Branch, Islamic Azad University Qazvin, Iran
Mohammad Reza Meybodi
Department of Computer engineering and IT Amirkabir University of Technology Tehran, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :