arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2312.01709math.OCcs.MScs.NAmath.NA
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一个新的具有挑战性的全局优化曲线拟合基准测试集

A New Challenging Curve Fitting Benchmark Test Set for Global Optimization

Peicong Cheng, Peicheng Cheng

AI总结:

本文提出新的PCC曲线拟合基准测试集,其维数小、无约束且难度高,经七个全局优化求解器测试,证明其比NIST基准更适合评估全局优化算法。

摘要:

基准测试集对于评估和开发全局优化算法及相关求解器极为重要。本文首次针对非线性曲线拟合的优化问题提出了一种名为PCC基准的新测试集,旨在帮助开发者研究和比较不同全局优化求解器的性能,并促进开发更有效的优化算法。与美国国家标准与技术研究院(NIST)给出的著名经典非线性曲线拟合基准集相比,PCC基准最显著的特点是问题维数小、无约束且搜索域自由,以及获得全局优化解的难度高,这使得PCC基准不仅适用于验证不同全局优化算法的有效性,而且更适合于验证和比较各种相关求解器。包括Baron、Antigone、Couenne、Lingo、Scip、Matlab-GA和1stOpt在内的七个世界领先的全局优化求解器被用于全面测试NIST和PCC基准的有效性和效率。结果表明,NIST基准相对简单,不适合用于全局优化测试,而PCC基准是一个独特、具有挑战性且有效的全局优化测试数据集。

英文摘要:

Benchmark sets are extremely important for evaluating and developing global optimization algorithms and related solvers. A new test set named PCC benchmark is proposed especially for optimization problems of nonlinear curve fitting for the first time, with the aspiration of helping developers to investigate and compare the performance of different global optimization solvers, as well as more effective optimization algorithms could be developed. Compared with the well-known classical nonlinear curve fitting benchmark set given by the National Institute of Standards and Technology (NIST) of USA, the most distinguishable features of the PCC benchmark are small problem dimensions, unconstrained with free search domain and high level of difficulty for obtaining global optimization solutions, which make the PCC benchmark be not only suitable for validating the effectiveness of different global optimization algorithms, but also more ideal for verifying and comparing various related solvers. Seven of the world's leading global optimization solvers, including Baron, Antigone, Couenne, Lingo, Scip, Matlab-GA and 1stOpt, are employed to test NIST and PCC benchmark thoroughly in terms of both effectiveness and efficiency. The results showed that the NIST benchmark is relatively simple and not suitable for global optimization testing, meanwhile the PCC benchmark is a unique, challenging and effective test dataset for global optimization.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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