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许瑜飞1 钱锋1 杨明磊1 杜文莉1 钟伟民1

(1.华东理工大学化工过程先进控制和优化技术教育部重点实验室, 上海 200237)


【关键词】 算法;鲸鱼优化算法;渣油加氢;动力学模型;参数估值;优化;


【基金资助】 国家科技支撑计划项目(2015BAF22B02); 国家自然科学基金项目(61422303,61590922); 中央高校基本科研业务费专项资金;

Improved whale optimization algorithm and its application in optimization of residue hydrogenation parameters

XU Yufei1 QIAN Feng1 YANG Minglei1 DU Wenli1 ZHONG Weimin1

(1.Key Laboratory of Advanced Control and Optimization for Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China 200237)

【Abstract】An improved whale algorithm (DEOBWOA) based on differential evolution (DE) and elite opposition-based learning is proposed to solve the problem that the intelligent optimization algorithm is easy to fall into the local optimum and the convergence precision in dealing with the nonlinear optimization problem is poor. The algorithm uses the opposing search initialization, elite opposition-based learning and combines with DE, which can improve the convergence precision and convergence speed of the whale optimization (WOA) algorithm effectively and improve the ability to jump out of local optimum. Eight standard test functions are used to do simulation experiment. The results show that DEOBWOA algorithm has a better performance than WOA, heterogeneous comprehensive learning particle swarm optimization (HCLPSO) and DE. Finally, the kinetic model of residue hydrogenation is established, but there are many typical nonlinear constraints in the process of residue hydrogenation. So DEOBWOA is used to optimize the kinetic model parameters of residue hydrogenation in a refinery residue, which indicates that the algorithm can deal with the practical engineering optimization problem.

【Keywords】 algorithm; whale optimization algorithm; residue hydrogenation; kinetic modeling; parameter estimation; optimization;


【Funds】 National Key Technology Research and Development Program of the Ministry of Science and Technology of China (2015BAF22B02); National Natural Science Foundation of China (61422303, 61590922); Fundamental Research Funds for the Central Universities of Ministry of Education of China;

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This Article


CN: 11-1946/TQ

Vol 69, No. 03, Pages 891-899

March 2018


Article Outline


  • Introduction
  • 1 Improved WOA
  • 2 Simulation results and analysis
  • 3 Application in parameter optimization of residue hydrogenation process
  • 4 Conclusion
  • References