Simultaneous heat transfer search for computationally expensive numerical optimization

In this work, we modify the Heat Transfer Search algorithm that has been proposed in literature to develop an efficient variant. The variant, Simultaneous Heat Transfer Search has been demonstrated on the fifteen single objective, bound constrained, computationally expensive benchmark functions that have been provided as part of one of the competitions in IEEE Congress on Evolutionary Computation 2016. It was observed that the proposed SHTS algorithm has a very low time complexity and is competitive to other algorithms in terms of its ability to determine the optimal solutions.