English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Consider a salesperson that must sell some quota of brushes in order to win a trip to Hawaii. This salesperson has a map (a weighted graph) in which each city has an attached demand specifying the number of brushes that can be sold in that city. What is the best route to take to sell the quota while traveling the least distance possible? Notice that unlike the standard traveling salesman problem, not only do we need to figure out the order in which to visit the cities, but we must decide the more fundamental question: which cities do we want to visit? In this paper we give the first approximation algorithms with poly-logarithmic performance guarantees for this problem, as well as for the slightly more general PCTSP problem of Balas, and a variation we call the "bank-robber problem" (also called the "orienteering problem" by Golden, Levi, and Vohra). We do this by providing an O(log^2 k) approximation to the k-MST problem which is defined as follows. Given an undirected graph on n nodes with non-negative edge weights and an integer k n, find the tree of least weight that spans k vertices. (If desired, one may specify in the problem a "root vertex" that must be in the tree as well.) Our result improves on the previous best bound of O(k^0.5) of Ravi et al. and comes quite close to the bound of O(log k) of Garg and Hochbaum for the special case of points in 2-dimensional Euclidean space.

Improved approximation guarantees for minimum-weight k-trees and prize-collecting salesmen