Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems<sup>*</sup>

摆亮; 王钧炎; 江永亨; 黄德先

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Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems^*

Updated：2026-01-06

- Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems^*
- Chinese Journal of Chemical Engineering Vol. 20, Issue 6, Pages: 1074-1080(2012)
- Affiliations：
  
  1. Department of Automation, Tsinghua University,Beijing,China,100084
  2. National Laboratory for Information Science and Technology, Tsinghua University,Beijing,China,100084
  3. Marvell Technology (Shanghai) Ltd,Shanghai,China,201203
- Author bio：
- Funds：
- DOI：
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- Published：2012
- Accepted：
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[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1074-1080.
DOI：

[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1074-1080. DOI：

摘要

Abstract

In this paper

an improved hybrid differential evolution-estimation of distribution algorithm (IHDE-EDA) is proposed for nonlinear programming (NLP) and mixed integer nonlinear programming (MINLP) models in engineering optimization fields.In order to improve the global searching ability and convergence speed

IHDE-EDA takes full advantage of differential information and global statistical information extracted respectively from differential evolution algorithm and annealing mechanism-embedded estimation of distribution algorithm.Moreover

the feasibility rules are used to handle constraints

which do not require additional parameters and can guide the population to the feasible region quickly.The effectiveness of hybridization mechanism of IHDE-EDA is first discussed

and then simulation and comparison based on three benchmark problems demonstrate the efficiency

accuracy and robustness of IHDE-EDA.Finally

optimization on an industrial-size scheduling of two-pipeline crude oil blending problem shows the practical applicability of IHDE-EDA.

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