Jianlin Zhang

Orcid: 0000-0001-7754-7889

Affiliations:
  • anzhou University of Technology, Lanzhou, China


According to our database1, Jianlin Zhang authored at least 16 papers between 2015 and 2024.

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

Timeline

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Bibliography

2024
Two cooperative constraint handling techniques with an external archive for constrained multi-objective optimization.
Memetic Comput., June, 2024

A constrained multi-objective evolutionary algorithm with Pareto estimation via neural network.
Expert Syst. Appl., March, 2024

A bi-population cooperative scatter search algorithm for distributed hybrid flow shop scheduling with machine breakdown.
Comput. Ind. Eng., 2024

A coevolutionary algorithm using Self-organizing map approach for multimodal multi-objective optimization.
Appl. Soft Comput., 2024

A multi-modal multi-objective evolutionary algorithm based on scaled niche distance.
Appl. Soft Comput., 2024

2023
A large-scale multi-objective evolutionary algorithm based on importance rankings and information feedback.
Artif. Intell. Rev., December, 2023

A coevolutionary constrained multi-objective algorithm with a learning constraint boundary.
Appl. Soft Comput., November, 2023

A dual-stage large-scale multi-objective evolutionary algorithm with dynamic learning strategy.
Expert Syst. Appl., September, 2023

A Pareto front estimation-based constrained multi-objective evolutionary algorithm.
Appl. Intell., May, 2023

A Grouping Cooperative Differential Evolution Algorithm for Solving Partially Separable Complex Optimization Problems.
Cogn. Comput., 2023

A multi-operator-based large-scale multi-objective optimization evolutionary algorithm.
Proceedings of the 3rd International Conference on Bioinformatics and Intelligent Computing, 2023

2022
An Angle-based Many-Objective evolutionary algorithm with Shift-based density estimation and sum of objectives.
Expert Syst. Appl., December, 2022

A constrained multi-objective optimization algorithm with two cooperative populations.
Memetic Comput., 2022

2021
A two-stage evolutionary strategy based MOEA/D to multi-objective problems.
Expert Syst. Appl., 2021

2015
A shuffled complex evolution algorithm with opposition-based learning for a permutation flow shop scheduling problem.
Int. J. Comput. Integr. Manuf., 2015

An improved shuffled complex evolution algorithm with sequence mapping mechanism for job shop scheduling problems.
Expert Syst. Appl., 2015


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