High-order explicit numerical methods for the one- and two-dimensional haptotaxis problems of tumor invasion

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Publicado en:Advances in Continuous and Discrete Models vol. 2025, no. 1 (Dec 2025), p. 174
Autor principal: Zhang, Lin
Otros Autores: Guo, Wenjuan, Ge, Yongbin
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Springer Nature B.V.
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Acceso en línea:Citation/Abstract
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100 1 |a Zhang, Lin  |u Guangzhou University, School of Mathematics and Information Science, Guangzhou, China (GRID:grid.411863.9) (ISNI:0000 0001 0067 3588) 
245 1 |a High-order explicit numerical methods for the one- and two-dimensional haptotaxis problems of tumor invasion 
260 |b Springer Nature B.V.  |c Dec 2025 
513 |a Journal Article 
520 3 |a High-precision numerical methods are developed for biomathematical models that describe various biotaxis problems of tumor invasion, facilitating an in-depth exploration of the underlying evolutionary mechanism of tumor invasion. In this paper, we construct a high-order explicit numerical method for solving haptotaxis models of tumor invasion. To incorporate the specific characteristics of the initial and no-flux boundary conditions for the haptotaxis models, we employ a high-order compact finite difference method to discretize the spatial derivatives, thereby obtaining a series of semi-discrete ordinary differential systems to approximate the solutions of these models. The strong stability-preserving (SSP) Runge-Kutta method is utilized in the semi-discrete ordinary differential systems to obtain the third-order accuracy in time. A high-order numerical integration method is used to design a positivity-preserving algorithm with spatially fourth-order accuracy guaranteed. The designed explicit method not only has high accuracy and good stability, but also has obvious positivity-preserving effect, which is more accurate and reliable than the numerical methods for this problem in the existing literature. To validate the performances of the proposed methods, several numerical examples are provided, and all sorts of complicated biotaxis dynamics for the haptotaxis models are simulated. 
653 |a Accuracy 
653 |a Finite volume method 
653 |a Tumors 
653 |a Partial differential equations 
653 |a Mathematical analysis 
653 |a Metastasis 
653 |a Finite difference method 
653 |a Boundary conditions 
653 |a Runge-Kutta method 
653 |a Numerical analysis 
653 |a Numerical integration 
653 |a Stability 
653 |a Numerical methods 
700 1 |a Guo, Wenjuan  |u Guangzhou University, School of Mathematics and Information Science, Guangzhou, China (GRID:grid.411863.9) (ISNI:0000 0001 0067 3588) 
700 1 |a Ge, Yongbin  |u Dalian Minzu University, School of Science, Dalian, China (GRID:grid.440687.9) (ISNI:0000 0000 9927 2735) 
773 0 |t Advances in Continuous and Discrete Models  |g vol. 2025, no. 1 (Dec 2025), p. 174 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
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