Table 1 Emergency material demand forecasting and model design summary.

From: A multi-objective optimization framework integrating ICSL deep learning for forecasting and scheduling emergency medical supply demand in public health emergencies

Data

Model design

Researchers

Data source

Forecast Content

Base model

Factors considered

Time

Cost

urgency

Sun et al.11

Case studies

Emergency material demand prediction

Fuzzy rough set model

  

–

Chen et al.12

Flood disaster data

Flood disaster material demand

MIP

√

√

–

Yang et al.13

Casualty data

Classification of emergency supplies

Regression-based model

√

 

–

Mohammadi et al.15

Government data

Emergency rescue supplies

Neural network

√

√

–

Ekici et al.16

Government data

Food demand

SEIR

√

√

–

Buyuktahtakn17

Government data

Supply logistics allocation

MIP

 

√

–

Guo et al.20

Multi-source data

Port emergency resources

Multi-objective particle swarm optimization algorithm

√

 

–

Wang et al.23

Government data

Multi-objective emergency resource

Multi-objective cellular genetic algorithm and the improved A* algorithm

√

 

√