Design/optimization with advanced simulated annealing

Abstract

The paper describes a global optimization method applicable to problems with both continuous or/and discrete design variables. The method integrates and improves Simulated Annealing, Genetic Algorithms, Tabu Search, and Quasi Monte Carlo optimization methods into a hybrid called here Advanced Simulated Annealing. The method is first validated by considering a test function with many local minima and a single global minimum, both with and without constraints. Then, the method is applied to a case with discrete design variables by optimizing a composite laminate. The potential for using the synthetic optimization method into an MDO environment is demonstrated and directions for further research are outlined.