An Accelerated Fixed-Point Algorithm Applied to Quadratic Convex Separable Knapsack Problems

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS Journal of Control Science and Engineering Pub Date : 2024-02-08 DOI:10.1155/2024/7602027
Atécio Alves, Jônatas O. L. Silva, L. C. Matioli, P. S. M. Santos, Sissy S. Souza
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Abstract

In this article, we propose a root-finding algorithm for solving a quadratic convex separable knapsack problem, which is more straightforward than existing methods and competitive in practice. Besides, we also present an extension of the proposal, which improves its computational time, and then we incorporate the accelerated Anderson’s and Aitken’s fixed-point algorithms to obtain better results. The algorithm only performs function evaluations. We present partial convergence results of the algorithm. Moreover, we illustrate superior computational results in medium and large problems as well as the applicability of the algorithm with real-life applications to show their efficiency.
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应用于二次凸可分离包问题的加速定点算法
在本文中,我们提出了一种求解二次凸可分离 knapsack 问题的寻根算法,它比现有方法更直接,在实践中也更有竞争力。此外,我们还对该算法进行了扩展,改进了其计算时间,并结合了加速的安德森算法和艾特肯定点算法,以获得更好的结果。该算法只进行函数求值。我们给出了算法的部分收敛结果。此外,我们还说明了中型和大型问题的卓越计算结果,以及该算法在实际应用中的适用性,以显示其效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Control Science and Engineering
Journal of Control Science and Engineering AUTOMATION & CONTROL SYSTEMS-
CiteScore
4.70
自引率
0.00%
发文量
54
审稿时长
19 weeks
期刊介绍: Journal of Control Science and Engineering is a peer-reviewed, open access journal that publishes original research articles as well as review articles in all areas of control science and engineering.
期刊最新文献
An Accelerated Fixed-Point Algorithm Applied to Quadratic Convex Separable Knapsack Problems An Accelerated Fixed-Point Algorithm Applied to Quadratic Convex Separable Knapsack Problems Retracted: Research on Nonlinear Time Series Processing Method for Automatic Building Construction Management Retracted: Design and Discussion on Information Management and Control System of Agricultural Machinery and Equipment Retracted: Robot Fault Detection Based on Big Data
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