Clarkson University researchers have developed a new mathematical tool that could make artificial intelligence systems more ...

This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting ...

Abstract: The Nelder-Mead simplex method is a well-known algorithm enabling the minimization of functions that are not available in closed-form and that need not be differentiable or convex.

This research proposes a novel hybrid metaheuristic optimization framework that combines the Aquila Optimization algorithm with the Sine-Cosine Optimizer to find equilibrium points of reacting ...

Multi-criteria decision-making (MCDM) presents a significant challenge in decision-making processes, aiming to ascertain optimal choice by considering multiple criteria. This paper proposes rank order ...

Abstract: Hyperspectral unmixing aims at identifying the hidden spectral signatures (or endmembers) and their corresponding proportions (or abundances) from an observed hyperspectral scene. Many ...

The problem of tensor completion has applications in healthcare, computer vision, and other domains. However, past approaches to tensor completion have faced a tension in that they either have ...

Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia. Operating a software company needs to run without pouring a lot of money. At the same time, company ...

Center on Stochastic Modeling, Optimization, and Statistics (COSMOS), The University of Texas at Arlington, Arlington, TX, USA. Quantitative decision analysis involves notions of comparison and ...