Weitian Tong

Tenure-track Assistant Professor

Georgia Southern University

United States

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Weitian Tong is a Tenure-track Assistant Professor at Georgia Southern University in the United States. His research areas include optimization algorithms, machine learning applications, and robust predictive modeling. Recent publications explore topics such as scheduling in manufacturing environments and air quality forecasting using advanced neural network techniques.

Articles (18)

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2025

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2022

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2021

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2021

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2021

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2020

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2020

Collaborators (2)

Kelin Luo

Assistant Professor of Teaching

University at Buffalo

UNITED STATES

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Peng Fu

Assistant Professor

Harrisburg University of Science and Technology

UNITED STATES

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Weitian Tong

Research Interests

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About

Articles (18)

An efficient polynomial-time approximation scheme for parallel multi-stage open shops

A deep reinforcement learning assisted adaptive genetic algorithm for flexible job shop scheduling

Data-driven robust two-stage ferry vehicle management at airports

A polynomial-time approximation scheme for an arbitrary number of parallel identical multi-stage flow-shops

Robust Transformer-based model for spatiotemporal PM <sub>2.5</sub> prediction in California

Unmasking the sky: high-resolution PM<sub>2.5</sub> prediction in Texas using machine learning techniques

Online generalized assignment problem with historical information

Online k-color spanning disk problems

PM<sub>2.5</sub> forecasting based on transformer neural network and data embedding

Learn from history for online bipartite matching

Online crowdsourced truck delivery using historical information

A polynomial-time approximation scheme for parallel two-stage flowshops under makespan constraint

A local search 4/3-approximation algorithm for the minimum 3-path partition problem

An improved approximation algorithm for the minimum common integer partition problem

Learning with self-attention for rental market spatial dynamics in the Atlanta metropolitan area

No-wait two-stage flowshop problem with multi-task flexibility of the first machine

Deep learning spatiotemporal air pollution data in China using data fusion

A polynomial-time approximation scheme for an arbitrary number of parallel two-stage flow-shops

Collaborators (2)

Kelin Luo

Peng Fu

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