2026-10-13T03:06:33Z https://www.scidb.cn/oai

10.57760/sciencedb.011oz 2026-09-13T20:12:53Z

2026-09-13 Numerical simulation dataset for a virtual-queue-based online convex optimization algorithm using Lyapunov optimization doi:10.57760/sciencedb.011oz en This dataset contains the numerical experiment results reported in the paper “Research on Online Convex Optimization Algorithms With Long-term Constraints Based on Lyapunov Optimization.” It includes the performance data of the proposed virtual-queue-based online convex optimization algorithm using Lyapunov optimization and the comparison algorithms proposed by Yi et al. (2021) and Yuan and Lamperski (2018) under three experimental settings: online linear programming with a known total number of rounds, online linear programming with an unknown total number of rounds, and a setting with strongly convex loss functions. The main performance metrics are cumulative loss and cumulative constraint violation. The reported results are averaged over 500 independent repetitions for each setting. The dataset can be used to reproduce the numerical results reported in the paper and to compare the performance of the algorithms. online convex optimization; long-term constraints; regret; cumulative constraint violation; Lyapunov opti mization shen lu ge PUBLIC https://creativecommons.org/publicdomain/zero/1.0/ dataset Science Data Bank