Most of you have used a navigation app like Google Maps for your travels at some point. These apps rely on algorithms that compute shortest paths through vast networks. Now imagine scaling that task ...

Abstract: In this paper, we consider the problem of finding the shortest path in a graph when there is aleatoric uncertainty about the presence and/or cost of certain edges. We investigate hybrid path ...

Abstract: Dynamic programming and greedy heuristics represent two core paradigms in autonomous path planning, each balancing optimality and computational effort in different ways. This work implements ...

A clear science explanation breaks down how lightning forms and why it branches through the air instead of traveling in a straight line to the ground. Labor to pass super tax changes with support of ...

Shortest path algorithms sit at the heart of modern graph theory and many of the systems that move people, data, and goods around the world. After nearly seventy years of relying on the same classic ...

When Edsger W. Dijkstra published his algorithm in 1959, computer networks were barely a thing. The algorithm in question found the shortest path between any two nodes on a graph, with a variant ...

Python simulation of the London Underground network that finds the fastest route between stations using weighted graph algorithms. Includes dynamic connections and optimization for travel time and ...

Rollercoaster Tycoon wasn’t the most fashionable computer game out there in 1999. But if you took a look beneath the pixels—the rickety rides, the crowds of hungry, thirsty, barfing people (and the ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...