JADE

JADE: adaptive differential evolution with optional external archive. A new differential evolution (DE) algorithm, JADE, is proposed to improve optimization performance by implementing a new mutation strategy ”DE/current-to-pbest” with optional external archive and updating control parameters in an adaptive manner. The DE/current-to- pbest is a generalization of the classic ”DE/current-to-best,” while the optional archive operation utilizes historical data to provide information of progress direction. Both operations diversify the population and improve the convergence performance. The parameter adaptation automatically updates the control parameters to appropriate values and avoids a user’s prior knowledge of the relationship between the parameter settings and the characteristics of optimization problems. It is thus helpful to improve the robustness of the algorithm. Simulation results show that JADE is better than, or at least comparable to, other classic or adaptive DE algorithms, the canonical particle swarm optimization, and other evolutionary algorithms from the literature in terms of convergence performance for a set of 20 benchmark problems. JADE with an external archive shows promising results for relatively high dimensional problems. In addition, it clearly shows that there is no fixed control parameter setting suitable for various problems or even at different optimization stages of a single problem.


References in zbMATH (referenced in 145 articles )

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  1. Liu, Qingxue; Du, Shengzhi; van Wyk, Barend Jacobus; Sun, Yanxia: Double-layer-clustering differential evolution multimodal optimization by speciation and self-adaptive strategies (2021)
  2. Platas-López, Alejandro; Mezura-Montes, Efrén; Cruz-Ramírez, Nicandro; Guerra-Hernández, Alejandro: Discriminative learning of Bayesian network parameters by differential evolution (2021)
  3. Ren, Hao; Li, Jun; Chen, Huiling; Li, ChenYang: Adaptive Lévy-assisted salp swarm algorithm: analysis and optimization case studies (2021)
  4. Salgotra, Rohit; Singh, Urvinder; Singh, Gurdeep; Mittal, Nitin; Gandomi, Amir H.: A self-adaptive hybridized differential evolution naked mole-rat algorithm for engineering optimization problems (2021)
  5. Smejkal, Tomáš; Mikyška, Jiří; Kukal, Jaromír: Comparison of modern heuristics on solving the phase stability testing problem (2021)
  6. Tan, Zhiping; Li, Kangshun; Wang, Yi: Differential evolution with adaptive mutation strategy based on fitness landscape analysis (2021)
  7. Xia, Xuewen; Gui, Ling; Zhang, Yinglong; Xu, Xing; Yu, Fei; Wu, Hongrun; Wei, Bo; He, Guoliang; Li, Yuanxiang; Li, Kangshun: A fitness-based adaptive differential evolution algorithm (2021)
  8. Baioletti, Marco; Milani, Alfredo; Santucci, Valentino: Variable neighborhood algebraic differential evolution: an application to the linear ordering problem with cumulative costs (2020)
  9. Chacón Castillo, Joel; Segura, Carlos: Differential evolution with enhanced diversity maintenance (2020)
  10. Chai, Xuzhao; Xiao, Junming; Zheng, Zhishuai; Zhang, Liang; Qu, Boyang; Yan, Li; et al.: UAV 3D path planning based on multi-population ensemble differential evolution (2020)
  11. Chen, Huiling; Wang, Mingjing; Zhao, Xuehua: A multi-strategy enhanced sine cosine algorithm for global optimization and constrained practical engineering problems (2020)
  12. Chen, Liming; Qiu, Haobo; Gao, Liang; Jiang, Chen; Yang, Zan: Optimization of expensive black-box problems via gradient-enhanced Kriging (2020)
  13. Chen, Xingqian; Song, Shuangbao; Ji, Junkai; Tang, Zheng; Todo, Yuki: Incorporating a multiobjective knowledge-based energy function into differential evolution for protein structure prediction (2020)
  14. Chen, Xi; Wei, Qinqi: Optimal-operation model and optimization method for hybrid energy system on large ship (2020)
  15. Elaziz, Mohamed Abd; Li, Lin; Jayasena, K. P. N.; Xiong, Shengwu: Multiobjective big data optimization based on a hybrid salp swarm algorithm and differential evolution (2020)
  16. Elsayed, Saber; Sarker, Ruhul; Essam, Daryl; Coello Coello, Carlos A.: Evolutionary approach for large-scale mine scheduling (2020)
  17. Gandhi, B. G. Rajeev; Bhattacharjya, R. K.: Differential evolution and its application in identification of virus release location in a sewer line (2020)
  18. Gao, Weifeng; Luo, Yuting; Xu, Jingwei; Zhu, Shengqi: Evolutionary algorithm with multiobjective optimization technique for solving nonlinear equation systems (2020)
  19. He, Yifan; Aranha, Claus: Solving portfolio optimization problems using MOEA/D and Lévy flight (2020)
  20. Jiang, Chen; Hu, Zhen; Liu, Yixuan; Mourelatos, Zissimos P.; Gorsich, David; Jayakumar, Paramsothy: A sequential calibration and validation framework for model uncertainty quantification and reduction (2020)

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