Differential evolution with tabu list for global optimization and its application to phase equilibrium and parameter estimation problems

摘要: Stochastic global optimization and their applications are attracting greater attention interest in the recent past as they provide better solutions with relatively less computational effort. Among many popular methods, differential evolution (DE), proposed by Storn Price [J. Global Optim. 1997, 11, 341−359], is a population-based direct search algorithm for nonlinear nondifferentiable functions, has found numerous due its simplicity, ease of use, faster convergence. In this work, we attempted to improve efficiency DE further implementing concept (i.e., avoiding revisits during search) tabu (TS) using list generation step DE; it also provides diversity among members population. (DETL) initially tested on several benchmark problems involving few thousands local minima 2−20 variables. It then challenging phase equilibrium calculations followed parameter...