A Hybrid Estimation of Distribution Algorithm and Nelder-Mead Simplex Method for Solving a Class of Nonlinear Bilevel Programming Problems

We propose a hybrid algorithm based on estimation of distribution algorithm (EDA) and Nelder-Mead simplex method (NM) to solve a class of nonlinear bilevel programming problems where the follower’s problem is linear with respect to the lower level variable. The bilevel programming is an NP-hard opti...

Full description

Saved in:
Bibliographic Details
Main Authors: Aihong Ren, Yuping Wang, Fei Jia
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2013/378568
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832564036956323840
author Aihong Ren
Yuping Wang
Fei Jia
author_facet Aihong Ren
Yuping Wang
Fei Jia
author_sort Aihong Ren
collection DOAJ
description We propose a hybrid algorithm based on estimation of distribution algorithm (EDA) and Nelder-Mead simplex method (NM) to solve a class of nonlinear bilevel programming problems where the follower’s problem is linear with respect to the lower level variable. The bilevel programming is an NP-hard optimization problem, for which EDA-NM is applied as a new tool aiming at obtaining global optimal solutions of such a problem. In fact, EDA-NM is very easy to be implementedsince it does not require gradients information. Moreover, the hybrid algorithm intends to produce faster and more accurate convergence. In the proposed approach, for fixed upper level variable, we make use of the optimality conditions of linear programming to deal with the follower’s problem and obtain its optimal solution. Further, the leader’s objective function is taken as the fitness function. Based on these schemes, the hybrid algorithm is designed by combining EDA with NM. To verify the performance of EDA-NM, simulations on some test problems are made, and the results demonstrate that the proposed algorithm has a better performance than the compared algorithms. Finally, the proposed approach is used to solve a practical example about pollution charges problem.
format Article
id doaj-art-ef2883e5a2fa4fb5bc9a7a050b295924
institution Kabale University
issn 1110-757X
1687-0042
language English
publishDate 2013-01-01
publisher Wiley
record_format Article
series Journal of Applied Mathematics
spelling doaj-art-ef2883e5a2fa4fb5bc9a7a050b2959242025-02-03T01:11:59ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/378568378568A Hybrid Estimation of Distribution Algorithm and Nelder-Mead Simplex Method for Solving a Class of Nonlinear Bilevel Programming ProblemsAihong Ren0Yuping Wang1Fei Jia2School of Computer Science and Technology, Xidian University, Xi’an 710071, ChinaSchool of Computer Science and Technology, Xidian University, Xi’an 710071, ChinaSchool of Science, Xidian University, Xi’an 710071, ChinaWe propose a hybrid algorithm based on estimation of distribution algorithm (EDA) and Nelder-Mead simplex method (NM) to solve a class of nonlinear bilevel programming problems where the follower’s problem is linear with respect to the lower level variable. The bilevel programming is an NP-hard optimization problem, for which EDA-NM is applied as a new tool aiming at obtaining global optimal solutions of such a problem. In fact, EDA-NM is very easy to be implementedsince it does not require gradients information. Moreover, the hybrid algorithm intends to produce faster and more accurate convergence. In the proposed approach, for fixed upper level variable, we make use of the optimality conditions of linear programming to deal with the follower’s problem and obtain its optimal solution. Further, the leader’s objective function is taken as the fitness function. Based on these schemes, the hybrid algorithm is designed by combining EDA with NM. To verify the performance of EDA-NM, simulations on some test problems are made, and the results demonstrate that the proposed algorithm has a better performance than the compared algorithms. Finally, the proposed approach is used to solve a practical example about pollution charges problem.http://dx.doi.org/10.1155/2013/378568
spellingShingle Aihong Ren
Yuping Wang
Fei Jia
A Hybrid Estimation of Distribution Algorithm and Nelder-Mead Simplex Method for Solving a Class of Nonlinear Bilevel Programming Problems
Journal of Applied Mathematics
title A Hybrid Estimation of Distribution Algorithm and Nelder-Mead Simplex Method for Solving a Class of Nonlinear Bilevel Programming Problems
title_full A Hybrid Estimation of Distribution Algorithm and Nelder-Mead Simplex Method for Solving a Class of Nonlinear Bilevel Programming Problems
title_fullStr A Hybrid Estimation of Distribution Algorithm and Nelder-Mead Simplex Method for Solving a Class of Nonlinear Bilevel Programming Problems
title_full_unstemmed A Hybrid Estimation of Distribution Algorithm and Nelder-Mead Simplex Method for Solving a Class of Nonlinear Bilevel Programming Problems
title_short A Hybrid Estimation of Distribution Algorithm and Nelder-Mead Simplex Method for Solving a Class of Nonlinear Bilevel Programming Problems
title_sort hybrid estimation of distribution algorithm and nelder mead simplex method for solving a class of nonlinear bilevel programming problems
url http://dx.doi.org/10.1155/2013/378568
work_keys_str_mv AT aihongren ahybridestimationofdistributionalgorithmandneldermeadsimplexmethodforsolvingaclassofnonlinearbilevelprogrammingproblems
AT yupingwang ahybridestimationofdistributionalgorithmandneldermeadsimplexmethodforsolvingaclassofnonlinearbilevelprogrammingproblems
AT feijia ahybridestimationofdistributionalgorithmandneldermeadsimplexmethodforsolvingaclassofnonlinearbilevelprogrammingproblems
AT aihongren hybridestimationofdistributionalgorithmandneldermeadsimplexmethodforsolvingaclassofnonlinearbilevelprogrammingproblems
AT yupingwang hybridestimationofdistributionalgorithmandneldermeadsimplexmethodforsolvingaclassofnonlinearbilevelprogrammingproblems
AT feijia hybridestimationofdistributionalgorithmandneldermeadsimplexmethodforsolvingaclassofnonlinearbilevelprogrammingproblems