first learning of human drivers, which then 'mutate` to CAVs, are trained to optimize routing policies with the implemented algorithm. When the training is finished, it uses raw results to compute a ...

Combinatorial optimisation is a fundamental field in applied mathematics and computer science that focuses on finding an optimal object from a finite set of objects. In this context, problems are ...

Abstract: To address the Vehicle Routing Problem with Time Windows (VRPTW), this paper presents a novel Dual Adaptive Genetic Algorithm (DAGA). While numerous metaheuristic algorithms have been ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.

If this is what AI is doing in its pre-school years, its teen years should be a scream. Google executives are trying to appear forthcoming and responsive about troubling responses from its Gemini ...

Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...

Created my own topology to set up static routing. Also implemented an "application" layer routing protocol which implements distance vector routing using Bellman-Ford algorithm.

We now have planes, trains, and automobiles. So is it really a big deal if you have to travel several hours to date someone? What’s the issue if you live in Maryland and want to see someone in Rhode ...

We now have planes, trains, and automobiles. So what’s the big deal if you have to travel a few hours to date someone? What’s the issue if you live in Maryland and want to see someone in New York, ...

This paper presents an efficient genetic algorithm for solving multiobjective transportation problem, assignment, and transshipment Problems. The proposed approach integrates the merits of both ...