CEC 13

Problem definitions and evaluation criteria for the CEC 2013 special session on real-parameter optimization. ... This special session is devoted to the approaches, algorithms and techniques for solving real parameter single objective optimization without making use of the exact equations of the test functions. We encourage all researchers to test their algorithms on the CEC’13 test suite which includes 28 benchmark functions. The participants are required to send the final results in the form at specified in the technical report to the organizers. The organizers will present an overall analysis and comparison based on these results. We will also use statistical tests on convergence performance to compare algorithms that eventually generate similar final solutions. Papers on novel concepts that help us in understanding problem characteristics are also welcome. The C and Matlab codes for CEC’13 test suite can be downloaded from the website given below: http://www.ntu.edu.sg/home/EPNSugan/index_files/CEC2013/CEC2013.htm


References in zbMATH (referenced in 63 articles )

Showing results 1 to 20 of 63.
Sorted by year (citations)

1 2 3 4 next

  1. Jakubik, Johannes; Binding, Adrian; Feuerriegel, Stefan: Directed particle swarm optimization with Gaussian-process-based function forecasting (2021)
  2. Li, Wei; Gong, Wenyin: Differential evolution with quasi-reflection-based mutation (2021)
  3. Peng, Hu; Zhu, Wenhua; Deng, Changshou; Wu, Zhijian: Enhancing firefly algorithm with courtship learning (2021)
  4. Ren, Hao; Li, Jun; Chen, Huiling; Li, ChenYang: Adaptive Lévy-assisted salp swarm algorithm: analysis and optimization case studies (2021)
  5. 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)
  6. Tan, Zhiping; Li, Kangshun; Wang, Yi: Differential evolution with adaptive mutation strategy based on fitness landscape analysis (2021)
  7. Tawhid, M. A.; Ibrahim, A. M.: Solving nonlinear systems and unconstrained optimization problems by hybridizing whale optimization algorithm and flower pollination algorithm (2021)
  8. 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)
  9. Zhou, Xinyu; Lu, Jiaxin; Huang, Junhong; Zhong, Maosheng; Wang, Mingwen: Enhancing artificial bee colony algorithm with multi-elite guidance (2021)
  10. Chacón Castillo, Joel; Segura, Carlos: Differential evolution with enhanced diversity maintenance (2020)
  11. Chen, Yang; Pi, Dechang: An innovative flower pollination algorithm for continuous optimization problem (2020)
  12. Huang, Jianqiang; Ma, Yan: Bat algorithm based on an integration strategy and Gaussian distribution (2020)
  13. Jiang, Ruiye; Yang, Ming; Wang, Songyan; Chao, Tao: An improved whale optimization algorithm with armed force program and strategic adjustment (2020)
  14. Liang, Jing; Li, Yaxin; Qu, Boyang; Yu, Kunjie; Hu, Yi: Mutation strategy selection based on fitness landscape analysis: a preliminary study (2020)
  15. Mu, Lei; Wang, Peng; Xin, Gang: Quantum-inspired algorithm with fitness landscape approximation in reduced dimensional spaces for numerical function optimization (2020)
  16. Yu, Helong; Zhao, Nannan; Wang, Pengjun; Chen, Huiling; Li, Chengye: Chaos-enhanced synchronized bat optimizer (2020)
  17. Zhang, Xinming; Wang, Doudou; Fu, Zihao; Liu, Shangwang; Mao, Wentao; Liu, Guoqi; Jiang, Yun; Li, Shuangqian: Novel biogeography-based optimization algorithm with hybrid migration and global-best Gaussian mutation (2020)
  18. Bajer, Dražen; Zorić, Bruno: An effective refined artificial bee colony algorithm for numerical optimisation (2019)
  19. Fister, Iztok; Iglesias, Andres; Galvez, Akemi; Del Ser, Javier; Osaba, Eneko; Perc, Matjaž; Slavinec, Mitja: Novelty search for global optimization (2019)
  20. Luo, Jie; Chen, Huiling; Heidari, Ali Asghar; Xu, Yueting; Zhang, Qian; Li, Chengye: Multi-strategy boosted mutative whale-inspired optimization approaches (2019)

1 2 3 4 next