Wednesday, September 18, 2024

[DMANET] Special session, Evolutionary Computation and Machine Learning in Humanitarian Logistics and Disaster Forecasting at EvoStar 2025 (Trieste, Italy, April 23-25 2025)

Dear Colleagues

We are happy to invite you to the EvoApps 2025 Special Session
in Evolutionary Computation and Machine Learning in Humanitarian Logistics
and Disaster Forecasting.

This special session explores how two major areas of artificial
intelligence, such as evolutionary computation and machine learning, can
improve natural disaster preparedness, response, and recovery and the
efficiency of humanitarian logistics.

Topics of Interest:

- Optimization of resource allocation in emergencies
- Prediction of natural disasters using deep learning and machine
learning
- Evacuation planning and shelter management
- Allocation and management of limited resources
- Early response and damage mitigation warning systems
- Prediction of climate change impact and frequency of extreme weather
events
- Disaster simulation and modeling systems using AI
- Optimization of air transport and drones in emergency situations
- Disease prediction and management models in emergency situations using
machine learning
- Structural damage estimation and prediction in buildings after natural
disasters
- Optimization of emergency communication networks
- Implementation of algorithms for coordinating rescue team

More Information: https://www.evostar.org/2025/evoapps/ecml-hldf/


**** Submission Details ****

Page limit: 14 pages, Springer LNCS format.

Submission link and details: https://www.evostar.org/2025/submit-paper/

**** Important Dates ****

Submission deadline: November 1, 2024 (AoE)

EvoStar: April 23-25, 2025
Trieste, Italy

Held as part of EvoStar https://www.evostar.org/2025/

****Organisers****
Mario A. Navarro
Universidad de Guadalajara, Mexico
mario.navarro@academicos.udg.mx

Diego Oliva
Universidad de Guadalajara, Mexico
diego.oliva@cucei.udg.mx

**********************************************************
*
* Contributions to be spread via DMANET are submitted to
*
* DMANET@zpr.uni-koeln.de
*
* Replies to a message carried on DMANET should NOT be
* addressed to DMANET but to the original sender. The
* original sender, however, is invited to prepare an
* update of the replies received and to communicate it
* via DMANET.
*
* DISCRETE MATHEMATICS AND ALGORITHMS NETWORK (DMANET)
* http://www.zaik.uni-koeln.de/AFS/publications/dmanet/
*
**********************************************************