A Hybrid Optimization Algorithm for Solving Constrained Engineering Design Problems

This paper introduces a new hybrid optimization procedure named GA-PSO-SQP for resolution constrained engineering design problems. Certifiable issues in the engineering field are typically expansive scale or nonlinear or constrained optimization problems, very well-designed numerical procedure is this way needed. This coupling is based on the genetic algorithm, the sequential quadratic programming and on the particle swarm optimization united with a projected gradient algorithm to deal constrained optimization problems. Numerical results based on well-known held back engineering design problems are reported and compared. The solutions acquired by the proposed technique are generally improved than those results given by other known methodologies in the open literature.