Simulated Annealing using an Adaptive Search Vector

Abstract

It is reported that simulated annealing (SA), which changes one design variable at a time, is effective when applied to high-dimensional continuous optimization problems. However, if a correlation exists among the design variables, it is not efficient to search each dimension. In this paper, we propose SA with a mechanism to determine an appropriate search direction according to the landscape of the given problems. Its effectiveness is verified for high-dimensional problems with correlation among design variables