Application of asynchronous DE with trigonometric mutation in engineering design problems

Abstract

Asynchronous Differential Evolution (ADE) algorithm, a variation of Differential Evolution (DE) algorithm works asynchronously. It supports parallel optimization and strong exploration because ADE algorithm updates the population instantly when a vector with better fitness is found. ADE working is quite similar to Differential Evolution (DE) except the instant population updation feature. In this paper trigonometric mutation embedded ADE (ADE-TMO), a hybridized algorithm is tested over four unconstrained engineering design problems.