Optimizing of Turning parameters Using Multi-Objective Genetic Algorithm

In this research, the turning parameters of steel are optimized via multi-objective genetic algorithm and multi-objective harmony research algorithm. These two algorithms are known as strong and powerful tools in optimization of engineering problems. The stock removal rate and surface roughness, as two main of output parameters are the target function and have been considered to be optimized. Since, there are two functions here; we can not use the ordinary optimization method with single-objective algorithm. In steel machining, the stock removal rate usually decreases with the surface finishing and visa versa. Therefore, it is necessary to define the weight of these parameters. In this paper the importance of each of these parameters are determined with weight sum method. In this research, the optimization methods to solve the problems via these two algorithms are discussed first. Then, the steel samples are machined and the output data are analyzed and optimized.