Abstract: Machine Learning (ML)-based optimization frameworks emerge as a promising technique for solving large-scale Mixed Integer Linear Programs (MILPs), as they can capture the mapping between ...

Abstract: Energy optimization is a critical challenge in wireless sensor networks (WSNs) due to its direct impact on the network lifetime. This paper proposes the use of the K-means algorithm combined ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning Denmark facing "decisive moment" ...

ABSTRACT: This article examines some of the properties of quasi-Fejer sequences when used in quasi-gradiental techniques as an alternative to stochastic search techniques for optimizing unconstrained ...

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer ...

This project uses ordinal optimization for computationally efficient sizing of a hybrid energy system containing PV panels, batteries, diesel generators, and an intermittent grid. It also utilizes ...

The objective of the 3D-SCALO problem is to assign the given components to optimal mounting surfaces and position them at the best locations, while satisfying the requirements for (1) heat dissipation ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

ABSTRACT: With the development of the domestic economy and the increase in household income, the demand for investment has been growing, and funds are widely favored for their safety and flexibility.