Manufacturing Technology Today

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Adaptive Genetic Algorithm Approach for Optimization of Multi Pass Turning Operations


Affiliations
1 Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu - 620 015, India
     

   Subscribe/Renew Journal


This paper proposes a new optimization technique based on Adaptive Genetic Algorithm (AGA) to solve multi-pass turning optimization problems. The objective function is to determine machining parameters by minimizing the unit production cost subjected to various practical machining constraints. The proposed Adaptive Genetic Algorithm scheme for optimization of multi-pass turning operation proves p be competent with Genetic Algorithm and Simulated Annealing.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 244

PDF Views: 0




  • Adaptive Genetic Algorithm Approach for Optimization of Multi Pass Turning Operations

Abstract Views: 244  |  PDF Views: 0

Authors

R. Siva Sankar
Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu - 620 015, India
P. Asokan
Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu - 620 015, India
S. Kumanan
Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu - 620 015, India
T. Selvaraj
Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu - 620 015, India

Abstract


This paper proposes a new optimization technique based on Adaptive Genetic Algorithm (AGA) to solve multi-pass turning optimization problems. The objective function is to determine machining parameters by minimizing the unit production cost subjected to various practical machining constraints. The proposed Adaptive Genetic Algorithm scheme for optimization of multi-pass turning operation proves p be competent with Genetic Algorithm and Simulated Annealing.