Engineering design problems usually include large-scale, nonlinear, or constrained optimization problems. Under a given circumstance, optimization methods aim to find the optimum solutions that give the extremum of a function. There are numerous methods for solving optimization problems. Some of these problems are solved by heuristic or evolutionary approaches. Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are two of the state-ofart heuristic optimization techniques. Additionally, one of the recently developed heuristic population-based optimization technique is the Sine-Cosine Algorithm. The pressure vessel design problem has been solved using various methods in the literature. Fruit Fly Algorithm gives the best minimum design cost, which is 5896.9489. In this work, the Sine-Cosine Algorithm was used to optimize the design cost of the pressure vessel and obtained 5888.5213, which is better than the literature’s best reported design cost.

Keywords : Genetic Algorithm, Particle Swarm Optimization, Sine - Cosine Algorithm, Pressure Vessel and American Society of Mechanical Engineers.