Abstract
In this paper, a new metaheuristic optimization algorithm based on the law of thermodynamics and heat transfer is introduced. In the proposed algorithm, the search agents are molecules of the system that interact with each other as well as with the surrounding to attain thermal equilibrium state. The interactions of molecules are through various modes of heat transfer (i.e. conduction, convection and radiation). The performance of the proposed algorithm is investigated by implementing it for the parameter optimization of 24 well defined constrained optimization problems of Congress on Evolutionary Computation 2006 (CEC 2006). The results obtained using the proposed algorithm are compared with the results of some well-known metaheuristic search algorithms available in the literature. The statistical analysis of the experimental work has been carried out by conducting Friedman's rank test and Holm post hoc procedure. The comparative results validate the competitive and efficient performance of the proposed algorithm for solving constraint optimization problems.
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