Open AccessLogistics Support Path Planning Model of Forest Fire Based on Ant Colony Algorithm
Author(s) -
Shuchao Tian,
Ziqing Zhou,
Zhihui Wang,
Xia Qing,
Zhehua Wen,
Baoxue Wang,
Ling Liu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1575/1/012118
Subject(s) - ant colony optimization algorithms , computer science , path (computing) , task (project management) , motion planning , node (physics) , set (abstract data type) , heuristic , time limit , function (biology) , ant colony , limit (mathematics) , mathematical optimization , algorithm , operations research , artificial intelligence , engineering , mathematics , systems engineering , robot , mathematical analysis , structural engineering , evolutionary biology , biology , programming language
The problem of the network node and the complex constrain in the path planning has become a difficulty in forest fire logistics support. The traditional ant colony algorithm is improved. We establish two objective functions for the distance between nodes and the time required to finish task. We optimize the two objective functions. We redesigned the calculation method of heuristic information and the update function of pheromone. We set a time window to limit the time to complete urgent tasks. Finally, an example is given for verification. The results show that the improved algorithm can solve the problem of logistics support path planning model of forest fire. The results are more close to the actual situation.