简介概要

An improved self-adaptive membrane computing optimization algorithm andits applications in residue hydrogenating model parameter estimation

来源期刊:中南大学学报(英文版)2015年第10期

论文作者:LU Hui-bin BO Cui-mei YANG Shi-pin

文章页码:3909 - 3915

Key words:optimization algorithm; membrane computing; benchmark function; improved self-adaptive operator

Abstract: In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing (ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied improved self-adaptive crossover and mutation formulae that can provide appropriate crossover operator and mutation operator based on different functions of the objects and the number of iterations. The performance of ISMC was tested by the benchmark functions. The simulation results for residue hydrogenating kinetics model parameter estimation show that the proposed method is superior to the traditional intelligent algorithms in terms of convergence accuracy and stability in solving the complex parameter optimization problems.

详情信息展示

An improved self-adaptive membrane computing optimization algorithm andits applications in residue hydrogenating model parameter estimation

LU Hui-bin(芦会彬), BO Cui-mei(薄翠梅), YANG Shi-pin(杨世品)

(College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China)

Abstract:In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing (ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied improved self-adaptive crossover and mutation formulae that can provide appropriate crossover operator and mutation operator based on different functions of the objects and the number of iterations. The performance of ISMC was tested by the benchmark functions. The simulation results for residue hydrogenating kinetics model parameter estimation show that the proposed method is superior to the traditional intelligent algorithms in terms of convergence accuracy and stability in solving the complex parameter optimization problems.

Key words:optimization algorithm; membrane computing; benchmark function; improved self-adaptive operator

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