Robust optimization using hybrid differential evolution and sequential quadratic programming

被引:22
作者
Cheng, Shuo [1 ]
Li, Mian [1 ]
机构
[1] Shanghai Jiao Tong Univ, Univ Michigan Shanghai Jiao Tong Univ Joint Inst, Shanghai 200030, Peoples R China
关键词
hybrid algorithm; interval uncertainty; SQP; robust optimization; DE; GLOBAL OPTIMIZATION; DESIGN; UNCERTAINTY;
D O I
10.1080/0305215X.2013.875164
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Although robust optimization can find solutions to engineering problems with uncertainty, the computational inefficiency of robust optimization methods is still a major concern. In this article, a new hybrid robust optimization method, namely differential evolution-sequential quadratic programming-robust optimization (DE-SQP-RO), is presented to find global robust optima for nonlinear robust optimization problems. The proposed algorithm is conducted under the structure of DE-RO, with SQP-RO acting as a local optimizer. Two criteria and switch indices are developed to indicate when the algorithm should switch from DE-RO to SQP-RO and vice versa. One numerical and two engineering examples are tested to demonstrate the applicability of the proposed algorithm. The results show that the hybrid algorithm uses 29-45% of the number of function evaluations required by DE-RO, and the robust solutions obtained by the hybrid algorithm are even better for certain examples.
引用
收藏
页码:87 / 106
页数:20
相关论文
共 50 条
  • [31] Hybridization of water wave optimization and sequential quadratic programming for cognitive radio system
    Singh, Gurmukh
    Rattan, Munish
    Gill, Sandeep Singh
    Mittal, Nitin
    SOFT COMPUTING, 2019, 23 (17) : 7991 - 8011
  • [32] A sequential quadratic programming algorithm for equality-constrained optimization without derivatives
    Anke Tröltzsch
    Optimization Letters, 2016, 10 : 383 - 399
  • [33] GPU Accelerated Sequential Quadratic Programming
    Hu, Xiukun
    Douglas, Craig C.
    Lumley, Robert
    Seo, Mookwon
    2017 16TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS TO BUSINESS, ENGINEERING AND SCIENCE (DCABES), 2017, : 3 - 6
  • [34] A Hybrid Estimation of Distribution Algorithm with Differential Evolution for Global Optimization
    Dong, Bing
    Zhou, Aimin
    Zhang, Guixu
    PROCEEDINGS OF 2016 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2016,
  • [35] Multi-material topology optimization for the transient heat conduction problem using a sequential quadratic programming algorithm
    Long, Kai
    Wang, Xuan
    Gu, Xianguang
    ENGINEERING OPTIMIZATION, 2018, 50 (12) : 2091 - 2107
  • [36] Differential Evolution in Robust Optimization Over Time Using a Survival Time Approach
    Guzman-Gaspar, Jose-Yair
    Mezura-Montes, Efren
    Dominguez-Isidro, Saul
    MATHEMATICAL AND COMPUTATIONAL APPLICATIONS, 2020, 25 (04)
  • [37] Optimization Strategies Based on Sequential Quadratic Programming Applied for a Fermentation Process for Butanol Production
    Adriano Pinto Mariano
    Caliane Bastos Borba Costa
    Dejanira de Franceschi de Angelis
    Francisco Maugeri Filho
    Daniel Ibraim Pires Atala
    Maria Regina Wolf Maciel
    Rubens Maciel Filho
    Applied Biochemistry and Biotechnology, 2009, 159
  • [38] A two-phase sequential algorithm for global optimization of the standard quadratic programming problem
    Judice, Joaquim
    Sessa, Valentina
    Fukushima, Masao
    JOURNAL OF GLOBAL OPTIMIZATION, 2024,
  • [39] A Mixed Coding Scheme of a Particle Swarm Optimization and a Hybrid Genetic Algorithm with Sequential Quadratic Programming for Mixed Integer Nonlinear Programming in Common Chemical Engineering Practice
    Chanthasuwannasin, Manatsanan
    Kottititum, Bundit
    Srinophakun, Thongchai
    CHEMICAL ENGINEERING COMMUNICATIONS, 2017, 204 (08) : 840 - 851
  • [40] A hybrid whale optimization algorithm based on modified differential evolution for global optimization problems
    Luo, Jun
    Shi, Baoyu
    APPLIED INTELLIGENCE, 2019, 49 (05) : 1982 - 2000