AnswerBun.com

Can we use reinforcement learning and convex optimization to solve an optimization problem?

Operations Research Asked by qinqinxiaoguai on August 19, 2021

For an optimization problem, there are multiple-type variables should be optimized. Can we use the convex optimization method to solve a subproblem of partial variables, and then, with the obtained results of the subproblem, solve the remaining subproblem of other variables by reinforcement learning?

2 Answers

You can use RL in any step. But problem is optimality check of solution which is explained above. Also you can solve your problem directly using RL such as RL for VRP. And you can read this blog which is about RL usage. By the way your question is too broad to give detailed answer.

Answered by kur ag on August 19, 2021

Not really, but approximately. By OR standards, a problem is "solved" once we manage to satisfy the KKT conditions. There is no machine learning algorithm to date that can consistently satisfy constraints. ML is designed to give pretty good approximations, and that's about it.

For instance, image recognition can be posed as a convex optimisation problem, and we all know how well ML works on those problems. That doesn't mean however that it will always work (and it doesn't), unlike an optimisation algorithm.

Answered by Nikos Kazazakis on August 19, 2021

Add your own answers!

Related Questions

Free solver for MINP problems

1  Asked on February 18, 2021 by dspinfinity

     

Flexible Job Shop with Preemption

0  Asked on January 15, 2021 by robert-hildebrand

         

Constraint programming resources

3  Asked on November 28, 2020 by joffrey-l

     

Pyomo variable creation dilemma

1  Asked on October 31, 2020 by ethan-deakins

 

Ask a Question

Get help from others!

© 2022 AnswerBun.com. All rights reserved. Sites we Love: PCI Database, MenuIva, UKBizDB, Menu Kuliner, Sharing RPP