A forest management planning strategy based on Leslie model and simulated annealing algorithm

Yuxuan Zhao; Yanlu Sun; He Jiang; Xuewen Li

doi:10.1117/12.2685930

28 July 2023 A forest management planning strategy based on Leslie model and simulated annealing algorithm

Yuxuan Zhao, Yanlu Sun, He Jiang, Xuewen Li

Proceedings Volume 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023); 1275645 (2023) https://doi.org/10.1117/12.2685930
Event: 2023 3rd International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2023), 2023, Tangshan, China

Abstract

Forest is the most important part of carbon sequestration, and lack of systematic management methods. Leslie population models are often used to predict changes in animal populations. In this paper, the Leslie population model is improved to enable it to describe the growth of trees. Then the simulated annealing algorithm (SAA) is used to solve the model to obtain the optimal forest management method. The results show that the Leslie-SAA model considers multi-directional conditions and gives the optimal cutting strategy. As a result, it is a feasible and practical method.

Citation Download Citation

Yuxuan Zhao, Yanlu Sun, He Jiang, and Xuewen Li "A forest management planning strategy based on Leslie model and simulated annealing algorithm", Proc. SPIE 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023), 1275645 (28 July 2023); https://doi.org/10.1117/12.2685930

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