Yanhong Feng

Orcid: 0000-0003-3493-834X

Affiliations:
  • Hebei GEO University, School of Information Engineering, Hebei Center for Ecological and Environmental Geology Research, Shijiazhuang, China
  • North China Electronic Power University, Baoding, Hebei, China (2006)
  • Shijiazhuang University of Economics, School of Information Engineering, China


According to our database1, Yanhong Feng authored at least 12 papers between 2014 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2022
A binary moth search algorithm based on self-learning for multidimensional knapsack problems.
Future Gener. Comput. Syst., 2022

2021
Monarch butterfly optimization: A comprehensive review.
Expert Syst. Appl., 2021

2019
Enhanced Moth Search Algorithm for the Set-Union Knapsack Problems.
IEEE Access, 2019

2018
Multi-strategy monarch butterfly optimization algorithm for discounted {0-1} knapsack problem.
Neural Comput. Appl., 2018

Solving 0-1 knapsack problems by chaotic monarch butterfly optimization algorithm with Gaussian mutation.
Memetic Comput., 2018

Solving randomized time-varying knapsack problems by a novel global firefly algorithm.
Eng. Comput., 2018

Opposition-based learning monarch butterfly optimization with Gaussian perturbation for large-scale 0-1 knapsack problem.
Comput. Electr. Eng., 2018

Binary Moth Search Algorithm for Discounted {0-1} Knapsack Problem.
IEEE Access, 2018

2017
Solving 0-1 knapsack problem by a novel binary monarch butterfly optimization.
Neural Comput. Appl., 2017

2016
A Novel Hybrid Cuckoo Search Algorithm with Global Harmony Search for 0-1 Knapsack Problems.
Int. J. Comput. Intell. Syst., 2016

2014
An Effective Hybrid Cuckoo Search Algorithm with Improved Shuffled Frog Leaping Algorithm for 0-1 Knapsack Problems.
Comput. Intell. Neurosci., 2014

An Improved Hybrid Encoding Cuckoo Search Algorithm for 0-1 Knapsack Problems.
Comput. Intell. Neurosci., 2014


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