An-Da Li

Orcid: 0000-0002-2111-8724

According to our database1, An-Da Li authored at least 12 papers between 2016 and 2024.

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

Timeline

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Bibliography

2024
An improved probability-based discrete particle swarm optimization algorithm for solving the product portfolio planning problem.
Soft Comput., February, 2024

2023
Multi-objective particle swarm optimization for key quality feature selection in complex manufacturing processes.
Inf. Sci., September, 2023

2022
An improved exponential EWMA chart for monitoring time between events.
Qual. Reliab. Eng. Int., 2022

Robust multi-response optimization considering location effect, dispersion effect, and model uncertainty using hybridization of NSGA-II and direct multi-search.
Comput. Ind. Eng., 2022

A decomposition-based multi-objective particle swarm optimization algorithm with a local search strategy for key quality characteristic identification in production processes.
Comput. Ind. Eng., 2022

2021
Self-information-based weighted CUSUM charts for monitoring Poisson count data with varying sample sizes.
Qual. Reliab. Eng. Int., 2021

Improved binary particle swarm optimization for feature selection with new initialization and search space reduction strategies.
Appl. Soft Comput., 2021

A Forward Search Inspired Particle Swarm Optimization Algorithm for Feature Selection in Classification.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021

2020
Multi-objective feature selection using hybridization of a genetic algorithm and direct multisearch for key quality characteristic selection.
Inf. Sci., 2020

Multiobjective feature selection for key quality characteristic identification in production processes using a nondominated-sorting-based whale optimization algorithm.
Comput. Ind. Eng., 2020

2019
Key quality characteristics selection for imbalanced production data using a two-phase bi-objective feature selection method.
Eur. J. Oper. Res., 2019

2016
Bi-objective variable selection for key quality characteristics selection based on a modified NSGA-II and the ideal point method.
Comput. Ind., 2016


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