@article{jgg20251312,
author={{Sy, Fall El Hadji Malick and Zakaria, Kehel and Rafika, Hajji and Gning, Tine Moustapha},
title={Optimization of Genetic Material Collection Missions Using A Gis Approach Based on the Dijkstra Algorithm and its Implementation on A Web Platform},
journal={Journal of Geosciences and Geomatics},
volume={13},
number={1},
pages={23--30},
year={2025},
url={https://pubs.sciepub.com/jgg/13/1/2},
issn={2373-6704},
abstract={Spatial Distribution Modeling and Gap Analysis of species are based essentially on the environmental and socio-economic characteristics of the specimen in question. It is therefore essential to have a mechanism for visiting a large number of sites with a high probability of the presence of genetic material in the shortest possible time. The specific aim of this project is to address the optimization of itineraries for a genetic material collection mission, based primarily on the use of shortest-path search algorithms, in particular Dijkstra's algorithm. The results of this study make it possible to ensure access to the germplasm while rationalizing the resources deployed and, consequently, the financial costs incurred. The whole process of finding the optimal route was made viable by its integration into a platform as a Web application serving as a guide for a genetic material collection mission.},
doi={10.12691/jgg-13-1-2}
publisher={Science and Education Publishing}
}