Abstract The problem of finding a point inRn, from which the sum-of-distances to a finite number of non-empty, closed, and convex sets is minimum is called the generalized Fermat-Torricelli Problem […]
Abstract The amount of data transferred over dedicated and non-dedicated network links has been increasing much faster than the increase in the network capacity. On the other hand, the current
A Two-Phase Dynamic Throughput Optimization Model for Big Data Transfers Read More »
Abstract Optimizing the hyper-parameters of a multi-layer perceptron (MLP) artificial neural network (ANN) is not a trivial task, and even today the trial-and-error approach is widely used. Many works have
Extending MLP ANN hyper-parameters Optimization by using Genetic Algorithm Read More »
Abstract Python has become the programming language of choice for research and industry projects related to data science, machine learning, and deep learning. Since optimization is an inherent part of
Pymoo: Multi-Objective Optimization in Python Read More »
