Paper
Genetic Algorithm for Multiobjective Optimization: Applied in High Speed Machining Milling Operation
- Authors:
- Hicham Mokhtari; Mohamed Arezki Mellal; Idir Belaidi; Said Alem; Sofiane Berrazouane; Mahdi Ouziala
- Abstract
- Genetic Algorithms (GAs) are general-purpose heuristic search algorithms that mimic the evolutionary process in order to find the fittest solutions. The algorithms were introduced by Holland in 1975. Since then, they have received growing interest due to their ability to discover good solutions quickly for complex searching and optimization problems. Simple genetic algorithms have been developed to solve the problems of multi objective optimization, such as NSGA II. The objective of this research is to apply the elitist non-dominated sorting GA (NSGA-II) for multi-objective optimization problems in case of high speed machining for the milling operation. The implemented model under Matlab, allows, from a considered space research. We have optimized the values of and , for an imposed Depth, while the production cost and time are minimized, under technical constrains of the production system.
- Keywords
- Multi-objective Optimization; Genetic Algorithm NSGA-II; Pareto Front; Milling Operation
- StartPage
- 28
- EndPage
- 31
- Doi