Efficient Algorithms and Lightweight Spanners in Graph Theory

The recent developments in graph theory and algorithms have seen significant advancements in the efficiency and applicability of various graph-related problems. Notably, there has been a surge in algorithms designed to handle negative edge weights, which has traditionally been a challenging area. Innovations in parallel and bidirectional search algorithms have also shown promise, particularly in scale-free networks where these methods demonstrate sublinear running times. Additionally, the field has seen improvements in the construction of spanners, which are crucial for network routing and approximation algorithms. These spanners are now lighter and more efficient, contributing to better performance in practical applications. The overall trend indicates a move towards more efficient, parallel, and lightweight solutions that can handle a broader range of graph properties and edge weights.

Sources

On generating $k$-factorable graphic sequences with connected (resp.no connected) $k$-factors

Low-degree spanning trees of $2$-edge-connected graphs in linear time

A Simple Parallel Algorithm with Near-Linear Work for Negative-Weight Single-Source Shortest Paths

Balanced Bidirectional Breadth-First Search on Scale-Free Networks

Uniform Sampling of Negative Edge Weights in Shortest Path Networks

Breaking the Bellman-Ford Shortest-Path Bound

All-Hops Shortest Paths

Lightweight Near-Additive Spanners

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