SCI和EI收录∣中国化工学会会刊

›› 2017, Vol. 25 ›› Issue (4): 442-452.DOI: 10.1016/j.cjche.2016.07.018

• Process Systems Engineering and Process Safety • Previous Articles     Next Articles

Nonlinear constrained optimization using the flexible tolerance method hybridized with different unconstrained methods

Alice Medeiros Lima1, Antonio José Gonçalves Cruz1,2, Wu Hong Kwong2   

  1. 1 Chemical Engineering Graduate Program, Federal University of São Carlos, Rodovia Washington Luiz, km 235-SP 310, São Carlos, SP 13565-905, Brazil;
    2 Department of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luiz, km 235-SP 310, São Carlos, SP 13565-905, Brazil
  • Received:2016-04-28 Revised:2016-07-31 Online:2017-06-03 Published:2017-04-28

Nonlinear constrained optimization using the flexible tolerance method hybridized with different unconstrained methods

Alice Medeiros Lima1, Antonio José Gonçalves Cruz1,2, Wu Hong Kwong2   

  1. 1 Chemical Engineering Graduate Program, Federal University of São Carlos, Rodovia Washington Luiz, km 235-SP 310, São Carlos, SP 13565-905, Brazil;
    2 Department of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luiz, km 235-SP 310, São Carlos, SP 13565-905, Brazil
  • 通讯作者: Alice Medeiros Lima

Abstract: This paper proposes the use of the flexible tolerance method (FTM) modified with scaling of variables and hybridized with different unconstrained optimization methods to solve real constrained optimization problems.The benchmark problems used to analyze the performance of the methods were taken from G-Suite functions.The original method (FTM) and other four proposed methods:(i) FTM with scaling of variables (FTMS),(ii) FTMS hybridized with BFGS (FTMS-BFGS),(iii) FTMS hybridized with modified Powell's method (FTMS-Powell) and (iv) FTMS hybridized with PSO (FTMS-PSO),were implemented.The success rates of the methods were 80%,100%,75%,95% and 85%,for FTM,FTMS,FTMS-BFGS,FTMS-Powell and FTMS-PSO,respectively.Numerical experiments including real constrained problems indicated that FTMS gave the best performance,followed by FTMSPowell and FTMS-PSO.Despite the inferior performance compared to FTMS and FTMS-Powell,the FTMS-PSO method presented some advantages since good different initial points could be obtained,which allow exploring different routes through the solution space and to escape from local optima.The proposed methods proved to be an effective way of improving the performance of the original FTM.

Key words: Flexible tolerance method, Modified Powell's method, BFGS, PSO, Scaling, Hybridization

摘要: This paper proposes the use of the flexible tolerance method (FTM) modified with scaling of variables and hybridized with different unconstrained optimization methods to solve real constrained optimization problems.The benchmark problems used to analyze the performance of the methods were taken from G-Suite functions.The original method (FTM) and other four proposed methods:(i) FTM with scaling of variables (FTMS),(ii) FTMS hybridized with BFGS (FTMS-BFGS),(iii) FTMS hybridized with modified Powell's method (FTMS-Powell) and (iv) FTMS hybridized with PSO (FTMS-PSO),were implemented.The success rates of the methods were 80%,100%,75%,95% and 85%,for FTM,FTMS,FTMS-BFGS,FTMS-Powell and FTMS-PSO,respectively.Numerical experiments including real constrained problems indicated that FTMS gave the best performance,followed by FTMSPowell and FTMS-PSO.Despite the inferior performance compared to FTMS and FTMS-Powell,the FTMS-PSO method presented some advantages since good different initial points could be obtained,which allow exploring different routes through the solution space and to escape from local optima.The proposed methods proved to be an effective way of improving the performance of the original FTM.

关键词: Flexible tolerance method, Modified Powell's method, BFGS, PSO, Scaling, Hybridization