论文标题
非线性编程求解器，用于不受约束和受限的优化问题：基准分析
Nonlinear Programming Solvers for Unconstrained and Constrained Optimization Problems: a Benchmark Analysis
论文作者
论文摘要
在本文中，我们提出了一组指南，以选择解决方案的求解器，以解决非线性编程问题。考虑到这一点，我们介绍了常用求解器的收敛性能的比较。比较涉及准确性，收敛速度和收敛速度。由于其在学术界和行业的研究团队中的流行，MATLAB被用作求解器的共同实施平台。我们的研究包括可以免费获得或需要许可的求解器，或者在文献中得到充分描述。此外，如果求解器允许选择不同的最佳搜索方法，我们会区分求解器。结果，我们研究了23种算法的性能来解决60个基准问题。为了丰富我们的分析，我们将通过更改每个求解器的内部设置来提高收敛速度和准确性。
In this paper we propose a set of guidelines to select a solver for the solution of nonlinear programming problems. With this in mind, we present a comparison of the convergence performances of commonly used solvers for both unconstrained and constrained nonlinear programming problems. The comparison involves accuracy, convergence rate, and convergence speed. Because of its popularity among research teams in academia and industry, MATLAB is used as common implementation platform for the solvers. Our study includes solvers which are either freely available, or require a license, or are fully described in literature. In addition, we differentiate solvers if they allow the selection of different optimal search methods. As result, we examine the performances of 23 algorithms to solve 60 benchmark problems. To enrich our analysis, we will describe how, and to what extent, convergence speed and accuracy can be improved by changing the inner settings of each solver.
