The Thermodynamic Particle Swarm Optimizer
Yu Wu, Yuanxiang Li, Xing Xu, Shen Peng · 2008
This paper has presented a novel optimization algorithm - thermodynamic particle swarm optimizers (TDPSO). It combines the simplified evolutionary equation and the thermodynamically strategy.The simplified equation without the velocity variable has drastically reduced computation costs to achieve faster convergence. Inspired by the free energy principle of the thermo-dynamical theoretics, TDPSO algorithm has defined the rating-based entropy (RE)concept and a component thermodynamic replacement(CTR) rule. These definitions are applied to control the optimal process and to achieve the potential of finding a global optimum. Compared with other improved PSO techniques, the experimental results describe how-to make the TDPSO benefit from the thermodynamics.