Optimization of Genetic Material Collection Missions Using A Gis Approach Based on the Dijkstra Algorithm and its Implementation on A Web Platform

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.

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Publication Details

Journal
Journal of Geosciences and Geomatics
Published
2025-02-23
DOI
https://doi.org/10.12691/jgg-13-1-2
Primary Topic
Evolutionary Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimization of Genetic Material Collection Missions Using A Gis Approach Based on the Dijkstra Algorithm and its Implementation on A Web Platform

Zakaria Kehel, Fall El Hadji Malick Sy, Hajji Rafika, Tine Moustapha Gning
Journal of Geosciences and Geomatics
Evolutionary Algorithms and Applications
article

Optimization of Genetic Material Collection Missions Using A Gis Approach Based on the Dijkstra Algorithm and its Implementation on A Web Platform

Zakaria Kehel, Fall El Hadji Malick Sy, Hajji Rafika, Tine Moustapha Gning
article en

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.

Journal of Geosciences and GeomaticsVol. 13(1)
Institut Agronomique et Vétérinaire Hassan II
Openalex Percentile: Top 99%
Evolutionary Algorithms and Applications
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