期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2012
卷号：2
期号：5
页码：29-34
出版社：International Journal of Soft Computing & Engineering
摘要：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.
