Solving Ceramic Grinding Optimization Problem by Adaptive Quantum Evolutionary Algorithm

Abstract

Advanced structural ceramics are widely used in engineering applications. They are useful due to high chemical inertness and sublimation temperature. Optimization of ceramic grinding process is essential as ceramics have high hardness and low surface toughness which can lead to large number of defects. The ceramic grinding optimization problem is formulated as non-linear constrained optimization problem. This paper proposes to solve the optimization problem by using a recently proposed real coded Adaptive Quantum inspired Evolutionary Algorithm. It is free from user selectable parameters in evolutionary operators as the same is determined adaptively. The proposed algorithm does not require mutation for maintaining diversity. The results also show that the proposed algorithm is fast and robust in comparison to the known state of art methods available for solving such problems.