Online TSP with Predictions

06/30/2022
by   Hsiao-Yu Hu, et al.
0

We initiate the study of online routing problems with predictions, inspired by recent exciting results in the area of learning-augmented algorithms. A learning-augmented online algorithm which incorporates predictions in a black-box manner to outperform existing algorithms if the predictions are accurate while otherwise maintaining theoretical guarantees even when the predictions are extremely erroneous is a popular framework for overcoming pessimistic worst-case competitive analysis. In this study, we particularly begin investigating the classical online traveling salesman problem (OLTSP), where future requests are augmented with predictions. Unlike the prediction models in other previous studies, each actual request in the OLTSP, associated with its arrival time and position, may not coincide with the predicted ones, which, as imagined, leads to a troublesome situation. Our main result is to study different prediction models and design algorithms to improve the best-known results in the different settings. Moreover, we generalize the proposed results to the online dial-a-ride problem.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/25/2022

A Universal Error Measure for Input Predictions Applied to Online Graph Problems

We introduce a novel measure for quantifying the error in input predicti...
research
05/28/2020

Better and Simpler Learning-Augmented Online Caching

Lykouris and Vassilvitskii (ICML 2018) introduce a model of online cachi...
research
10/06/2022

Paging with Succinct Predictions

Paging is a prototypical problem in the area of online algorithms. It ha...
research
05/18/2022

Customizing ML Predictions for Online Algorithms

A popular line of recent research incorporates ML advice in the design o...
research
07/26/2022

Learning-Augmented Maximum Flow

We propose a framework for speeding up maximum flow computation by using...
research
01/30/2023

Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints

We consider non-clairvoyant scheduling with online precedence constraint...
research
02/14/2023

Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis

In this paper, we present improved learning-augmented algorithms for the...

Please sign up or login with your details

Forgot password? Click here to reset