Adaptive Exact Penalty Design for Optimal Resource Allocation. Academic Article

abstract

• In this article, a distributed adaptive continuous-time optimization algorithm based on the Laplacian-gradient method and adaptive control is designed for resource allocation problem with the resource constraint and the local convex set constraints. In order to deal with local convex sets, a distance-based exact penalty function method is adopted to reformulate the resource allocation problem instead of the widely used projection operator method. By using the nonsmooth analysis and set-valued LaSalle invariance principle, it is proven that the proposed algorithm is capable of solving the nonsmooth resource allocation problem. Finally, two simulation examples are presented to substantiate the theoretical results.

authors

• Huang, Tingwen

published proceedings

• IEEE Trans Neural Netw Learn Syst

altmetric score

• 0.25

author list (cited authors)

• Lian, M., Guo, Z., Wang, X., Wen, S., & Huang, T.

citation count

• 3

complete list of authors

• Lian, Mengke||Guo, Zhenyuan||Wang, Xiaoxuan||Wen, Shiping||Huang, Tingwen

publication date

• March 2023

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• n2162-237XISSN  Journal

keywords

• Adaptive Algorithm
• Cost Function
• Distributed Optimization
• Eigenvalues And Eigenfunctions
• Heuristic Algorithms
• Laplace Equations
• Learning Systems
• Linear Programming
• Nonsmooth Analysis
• Resource Allocation
• Resource Management

PubMed Central ID

• 34464266

Digital Object Identifier (DOI)

• 10.1109/TNNLS.2021.3105385

start page

• 1430

end page

• 1438

volume

• 34

issue

• 3

URL

• http://dx.doi.org/10.1109/tnnls.2021.3105385