학술논문

An improved evolution based optimization algorithm originated from the concept of SFLA and simulated annealing
Document Type
Conference
Source
2016 11th International Conference on Industrial and Information Systems (ICIIS) Industrial and Information Systems (ICIIS), 2016 11th International Conference on. :193-198 Dec, 2016
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Sociology
Statistics
Simulated annealing
Genetic algorithms
Temperature
Algorithm design and analysis
Optimization
Evolution
Global Optimality
PSO
Memetic
Simulated Annealing
Language
Abstract
The paper shows the contribution of evolutionary techniques in the field of optimization. Evolution is a technique which is based on real-world scenarios. It works on Darwin's theory and many algorithms have been proposed in this field to optimize the results. Each algorithm proposed has its advantages and disadvantages and a new technique is brought to overcome the drawbacks of the previously proposed technique. In this paper, a new approach is proposed based on SFLA and simulated annealing which works on memetic and PSO approaches along with basic temperature idea of simulated annealing. The graphs are attached to show the various results obtained. It is shown that it is better than other algorithms in various factors.