Ideal Gas Optimization Algorithm
This paper introduces a novel optimization algorithm which is inspired by the first law of thermodynamics and kinetic theory. In the proposed algorithm, named ideal gas optimization (IGO) algorithm, the searcher agents are a collection of molecules with pressure and temperature. In each iteration, molecules are clustered into several gas systems. IGO uses the interaction between gas systems and also between molecules to search the problem space for finding sub-optimum. The ability of the new algorithm is demonstrated using standard benchmark functions. The comparison of the results with Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA) shows the efficiency of the proposed algorithm.
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