Comparing existing tools in Python for modelling real-life optimisation problems with differential equations

Jingzhao Shu

doi:10.1117/12.2627658

22 April 2022 Comparing existing tools in Python for modelling real-life optimisation problems with differential equations

Jingzhao Shu

Author Affiliations +

Proceedings Volume 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021); 121632C (2022) https://doi.org/10.1117/12.2627658
Event: International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 2021, Nanjing, China

Abstract

Nowadays, more and more people have already realised that optimisation issues constrained by Differential and Algebraic Equations (DAEs) or Partial Differential and Algebraic Equations (PDAEs) are extremely important to our daily lives, as applications of this type of problem are very widely spread. Unfortunately, it is hard to solve these problems and therefore standard optimisation tools are needed to make them be convenient to deal with. It is clear that there are way too many algebraic modeling tools built into high-level programming languages, such as Python and MATLAB. Consequently, additional freedom was allowed by these tools in incorporating new elements, language, and workflows. The purpose of this article is to encourage model solvers to be able to use the most suitable tools in different situations, which including the advantages and disadvantages of existing tools for solving differential equations, to give them a comprehensive summary of performance of those tools. According to the research result, Pyomo.dae is the stable and flexible feature9, which is useful for modal transformations. Besides, Pyomo.dae is also suitable for three different differential equations. In addition, the Pymanopt can be used for automated differentiation when being applied in optimaisation on manifolds. The PyDEns is so flexible for convenient experimentation that it is famous for its applications for neural networks. At last, Pandapower is good at handling parameters.

Citation Download Citation

Jingzhao Shu "Comparing existing tools in Python for modelling real-life optimisation problems with differential equations", Proc. SPIE 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 121632C (22 April 2022); https://doi.org/10.1117/12.2627658

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