2025年1月10日 · In this paper, we develop quantile allocation models to examine how much the output and productivity could potentially increase if the resources were efficiently allocated between units. We increase robustness to random noise and heteroscedasticity by utilizing the local estimation of multiple production functions using convex quantile regression.

2023年6月13日 · Abstract: This article is concerned with the distributed optimal resource allocation problem with local feasibility constraints for high-order multiagent systems (MASs) over weight-balanced digraphs. Generally, the local feasibility constraints are addressed based on the feasible direction, determined by some time-dependent discontinuous functions.

5 天之前 · In this article, a momentum-based multiagent optimization approach is developed for distributed nonconvex optimal resource allocation. The proposed resource allocation model is formulated without the convex conditions, and a paradigmatic system based on the gradient descent with momentum method is proposed for handling its functional nonconvexity. Based on the paradigmatic system, a momentum ...

Resource allocation Introduction • Divide and conquer starts with the entire problem,, divides it into subproblems and then combines them into a solution – This is a top-down approach • Dynamic programming starts with the smallest, simplest subproblems and …

2025年1月1日 · By using multiple nodes, distributed algorithms can make better use of available resources, as each node can leverage its local resources more efficiently. Furthermore, distributed algorithms can facilitate decentralization and parallelizability, which is more efficient in scenarios where a central point of control may not be practical, cost ...

2024年12月11日 · By integrating the tracking controller design with global resource allocation optimization, fully distributed state-feedback controllers are proposed to solve optimization problems with output-based local objective functions.

2024年5月1日 · Efficient resource allocation strategies are crucial for ensuring smooth interactions among heterogeneous local-edge-cloud architectures. The strategy should aim to optimize the performance of multi-type service provision while taking into account factors such as latency, resource utilization, and energy consumption.

We in-crease robustness to random noise and heteroscedasticity by resorting to local esti-mation of multiple production functions using the convex quantile regression. Our em-pirical results...

Within D2D communication, resource allocation stands out as a critical research area aimed at enhancing the capabilities of 5G communication for IoT applications. In our proposed work, we begin by establishing a mathematical framework designed to minimize energy consumption in the allocation of frequency bands, utilizing a novel algorithm.

2020年1月7日 · In this study, the distributed optimisation for solving resource allocation problem with both local bound and equality constraints is studied. A continuous-time multi-agent system with communication time-delay is proposed for the resource allocation.