An improved heat transfer search algorithm for unconstrained optimization problems

In this work, an improved heat transfer search (IHTS) algorithm is proposed by incorporating the effect of the simultaneous heat transfer modes and population regeneration in the basic HTS algorithm. The basic HTS algorithm considers only one of the modes of heat transfer (conduction, convection, and radiation) for each generation. In the proposed algorithms, however, the system molecules are considered as the search agents that interact with each other as well as with the surrounding to a state of the thermal equilibrium. Another improvement is the integration of a population regenerator to reduce the probability of local optima stagnation. The population regenerator is applied to the solutions without improvements for a pre-defined number of iterations. The feasibility and effectiveness of the proposed algorithms are investigated by 23 classical benchmark functions and 30 functions extracted from the CEC2014 test suite. Also, two truss design problems are solved to demonstrate the applicability of the proposed algorithms. The results show that the IHTS algorithm is more effective as compared to the HTS algorithm. Moreover, the IHTS algorithm provides very competitive results compared to the existing meta-heuristics in the literature.