Quantum Inspired Evolutionary Algorithm for Optimization of Hot Extrusion Process
Rajat Setia1, K. Hans Raj2
1Rajat Setia, Department of Mechanical Engineering, Faculty of Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, India.
2K. Hans Raj, Department of Mechanical Engineering, Faculty of Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, India.
Manuscript received on November 01, 2012. | Revised Manuscript received on November 02, 2012. | Manuscript published on November 05, 2012. | PP: 29-34 | Volume-2 Issue-5, November 2012. | Retrieval Number: E0985092512/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Quantum Inspired Evolutionary Algorithm (QIEA) is a probability based optimization algorithm which applies quantum computing principles such as qubits, superposition, quantum gate and quantum measurement to enhance the properties of classical evolutionary algorithms. This work presents the application of QIEA, for the optimization of hot extrusion process i.e., for finding optimum value of die angle, co-efficient of friction and temperature of billet for minimizing the extrusion load. The optimal process parameters are compared with Finite Element (FE) simulation results conducted in FORGE-3 environment, which is a domain specific software designed to simulate hot, warm and cold forging. The results show the efficacy of QIEA in terms of good global search ability and fast convergence to the best solution due to its highly probabilistic nature and better characteristics of population diversity since it can represent linear superposition of states.
Keywords: Finite Element Simulation, FORGE-3, Optimization, QIEA.