Solving the Online Assignment Problem with Machine Learned Advice

The online assignment problem plays an important role in operational research and computer science which is why immense attention has been given to improving its solution quality. Due to the incomplete information about the input, it is difficult for online algorithms to produce the optimal solution. The quality of the solution of an online algorithm is measured using a competitive ratio. No online deterministic algorithm can achieve a competitive ratio better than (2n-1). It has been shown that advice in online computation improves the lower bound of the competitive ratio of online problems. Advice in online computation can be interpreted as additional information for the online algorithm to compensate for the lack of information about the whole input sequence. In this study, we investigate how introducing machine-learned advice could improve the competitive ratio for this problem. We provide an online algorithm for the online assignment problem by simulating a machine learning algorithm that predicts the whole input in advance. We utilize an optimal offline algorithm to provide a matching solution from the predicted input. Furthermore, we investigate how the prediction error of machine learning affects the competitive ratio of the online algorithm. We utilize a benchmark data set to perform our empirical analysis. We show that as the Machine Learning prediction error increases, the solution quality decreases. Moreover, the magnitude of error is directly proportional to the size of the input. This result is analogous to the competitive ratio of the best deterministic algorithm for the online assignment problem which is dependent also on the parameter n.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/01/2022

Online Unit Profit Knapsack with Untrusted Predictions

A variant of the online knapsack problem is considered in the settings o...
research
10/27/2019

Near-Optimal Bounds for Online Caching with Machine Learned Advice

In the model of online caching with machine learned advice, introduced b...
research
12/17/2020

Metrical Task Systems with Online Machine Learned Advice

Machine learning algorithms are designed to make accurate predictions of...
research
09/03/2020

New Results and Bounds on Online Facility Assignment Problem

Consider an online facility assignment problem where a set of facilities...
research
05/08/2023

Online Task Assignment with Controllable Processing Time

We study a new online assignment problem, called the Online Task Assignm...
research
08/09/2023

Controlling Tail Risk in Online Ski-Rental

The classical ski-rental problem admits a textbook 2-competitive determi...
research
02/15/2018

Competitive caching with machine learned advice

Traditional online algorithms encapsulate decision making under uncertai...

Please sign up or login with your details

Forgot password? Click here to reset