Kim, Sung Soo and Kim, Il-Hwan and Mani, V and Kim, Hyung Jun (2008) Real-coded genetic algorithm for machining condition optimization. In: International Journal of Advanced Manufacturing Technology, 38 (9-10). pp. 884-895.
fulltext.pdf - Published Version
Restricted to Registered users only
Download (252Kb) | Request a copy
In this paper, we consider the machining condition optimization models presented in earlier studies. Finding the optimal combination of machining conditions within the constraints is a difficult task. Hence, in earlier studies standard optimization methods are used. The non-linear nature of the objective function, and the constraints that need to be satisfied makes it difficult to use the standard optimization methods for the solution. In this paper, we present a real coded genetic algorithm (RCGA), to find the optimal combination of machining conditions. We present various issues related to real coded genetic algorithm such as solution representation, crossover operators, and repair algorithm in detail. We also present the results obtained for these models using real coded genetic algorithm and discuss the advantages of using real coded genetic algorithm for these problems. From the results obtained, we conclude that real coded genetic algorithm is reliable and accurate for solving the machining condition optimization models.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Springer.|
|Keywords:||Machining conditions;Multi-pass turning;Optimization;Real-coded genetic algorithm; Single-pass turning.|
|Department/Centre:||Division of Mechanical Sciences > Aerospace Engineering (Formerly, Aeronautical Engineering)|
|Date Deposited:||30 Mar 2010 07:09|
|Last Modified:||19 Sep 2010 05:58|
Actions (login required)