Abstract
Based on Newton’s law of cooling, Kaveh and Dadras [1] introduced a new metaheuristic named Thermal Exchange Optimization (TEO) algorithm. TEO is in early stages of its use and is utilized to solve a few structural optimization problems [2, 3]. Newton’s law of cooling states that the rate of heat loss of a body is proportional to the difference in temperatures between the body and its surroundings. TEO considers each of its particles as a cooling or heating object, and by associating another agent as the environment, a heat transferring and thermal exchange happens between them. The new temperature of the object is considered as its next position in the search space.
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