A Variant of the Sine Cosine Algorithm for Engineering Optimization Design

The design of pressure vessels is a constrained optimization problem that is influenced by many real-world standards and specifications. It involves multiple variables and multiple constraints. The existence of real constraints can make the solution space complex, leading to multiple local optima and making the search for the global optimum very difficult. Metaheuristic algorithms provide effective solutions for constrained optimization problems. The Sine Cosine Algorithm (SCA) is an optimization algorithm based on sine and cosine functions. However, like most metaheuristic algorithms, the traditional SCA has some shortcomings, such as high dependence on the initial solution and the tendency to get trapped in local optima. In this paper, we address these issues by using the Singer chaotic mapping to initialize the solution space of the population and introducing quantum theory to improve the search mechanism of the SCA algorithm. We propose a variant of SCA called CQ-SCA for optimizing the weight design of pressure vessels. Experimental results show that the design scheme obtained by CQ-SCA is more suitable than other algorithms.