Mdthbs

Wearing special clothes in public while in niddah- isn't this a lack of tznius?

Is there a minimum amount of electricity that can be fed back into the grid?

Park the computer

Who goes first? Person disembarking bus or the bicycle?

Is it acceptable that I plot a time-series figure with years increasing from right to left?

Examples of fluid (including air) being used to transmit digital data?

How would a sea turtle end up on its back?

Groups where no elements commute except for the trivial cases

Gory anime with pink haired girl escaping an asylum

Shipped package arrived - didn't order, possible scam?

An easy way to solve this limit of a sum?

Is conquering your neighbors to fight a greater enemy a valid strategy?

Does a Globe of Invulnerability spell block outsiders from teleporting inside with a spell?

Are "confidant" and "confident" homophones?

How do I talk to my wife about unrealistic expectations?

What was the significance of Spider-Man: Far From Home being an MCU Phase 3 film instead of a Phase 4 film?

Taking my Ph.D. advisor out for dinner after graduation

Can a USB hub be used to access a drive from two devices?

Multi-user CRUD: Valid, Problem, or Error?

comparing two addresses

How to play a D major chord lower than the open E major chord on guitar?

Why do most airliners have underwing engines, while business jets have rear-mounted engines?

My professor has told me he will be the corresponding author. Will it hurt my future career?

Well-ordered Cartesian product in ZF

Examples of machine learning applied to operations research?

What is the connection of Operations Research and Reinforcement Learning?What are the tradeoffs between “exact” and Reinforcement Learning methods for solving optimization problemsAs an Operations Research professional, how is your time divided when working on an optimization project?

2

$begingroup$

Can someone give me a few examples, if they exist, of problems in operations research that could be solved using machine learning.

I am aware that machine learning examples are data-driven and do not give exact solutions, so I am expecting heuristics, and possibly solutions that are specific for a particular instance of the problem.

I am looking for 'direct' machine learning solutions that use machine learning to find a solution of the actual problem, and not just 'indirect' approaches that try to improve existing methods.

EDIT:
I am looking for examples in which the ML approach outperforms other methods.

modeling machine-learning

share|improve this question

edited 7 hours ago

klaus

asked 8 hours ago

klausklaus

11133 bronze badges

New contributor

klaus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

2

$begingroup$

Can someone give me a few examples, if they exist, of problems in operations research that could be solved using machine learning.

I am aware that machine learning examples are data-driven and do not give exact solutions, so I am expecting heuristics, and possibly solutions that are specific for a particular instance of the problem.

I am looking for 'direct' machine learning solutions that use machine learning to find a solution of the actual problem, and not just 'indirect' approaches that try to improve existing methods.

EDIT:
I am looking for examples in which the ML approach outperforms other methods.

modeling machine-learning

share|improve this question

edited 7 hours ago

klaus

asked 8 hours ago

klausklaus

11133 bronze badges

New contributor

klaus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

Can someone give me a few examples, if they exist, of problems in operations research that could be solved using machine learning.

I am aware that machine learning examples are data-driven and do not give exact solutions, so I am expecting heuristics, and possibly solutions that are specific for a particular instance of the problem.

I am looking for 'direct' machine learning solutions that use machine learning to find a solution of the actual problem, and not just 'indirect' approaches that try to improve existing methods.

EDIT:
I am looking for examples in which the ML approach outperforms other methods.

modeling machine-learning

share|improve this question

edited 7 hours ago

klaus

asked 8 hours ago

klausklaus

11133 bronze badges

New contributor

klaus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share|improve this question

edited 7 hours ago

klaus

asked 8 hours ago

klausklaus

11133 bronze badges

New contributor

klaus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

edited 7 hours ago

klaus

asked 8 hours ago

klausklaus

11133 bronze badges

New contributor

klaus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 8 hours ago

klausklaus

11133 bronze badges

New contributor

klaus is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 8 hours ago

klausklaus

11133 bronze badges

2 Answers
2

active

oldest

votes

2

$begingroup$

Using OR in ML is a very popular approach due to the optimization nature lying behind ML.

However, as you ask, there are also many examples (younger, newer) where you apply ML to solve OR problems. For example, for routing problems: https://arxiv.org/pdf/1803.08475.pdf

The list can be appended, but I think your question needs to be improved before.

share|improve this answer

answered 8 hours ago

independentvariableindependentvariable

66411 silver badge1414 bronze badges

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  The paper you cited has quite a few examples in the related work section. However they claim that "The goal of our method is not to outperform a non- learned, specialized TSP algorithm such as Concorde...". I edited my question to narrow my search for examples that do outperform non-learned algorithms.
  $endgroup$
  – klaus
  7 hours ago
  

  
  
  
  

add a comment | 

0

$begingroup$

There is a paper Learning Fast Optimizers for Contextual Stochastic Integer Programs where they develop a "learnable local solver" to solve problems where the MIP solvers did not scale.

I have not studied the paper, yet, but it may fit your bill.

share|improve this answer

answered 22 mins ago

Robert SchwarzRobert Schwarz

44622 silver badges77 bronze badges

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  The problems are two-stage stochastic optimization, where the learned local solver is applied to the first stage, after which the (deterministic) second stage is handed to a MIP solver. This performs better than handing the overall problem to a MIP solver (better objective within same time limit).
  $endgroup$
  – Robert Schwarz
  20 mins ago
  

  
  
  
  

add a comment | 

Your Answer

StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "700"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);

StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});

function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
noCode: true, onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});


}
});

klaus is a new contributor. Be nice, and check out our Code of Conduct.

draft saved

draft discarded

Sign up or log in

StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});

Sign up using Google

Sign up using Facebook

Sign up using Email and Password

Post as a guest

Name

Email

Required, but never shown

StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2for.stackexchange.com%2fquestions%2f889%2fexamples-of-machine-learning-applied-to-operations-research%23new-answer', 'question_page');
}
);

Post as a guest

Name

Email

Required, but never shown

2

$begingroup$

Using OR in ML is a very popular approach due to the optimization nature lying behind ML.

However, as you ask, there are also many examples (younger, newer) where you apply ML to solve OR problems. For example, for routing problems: https://arxiv.org/pdf/1803.08475.pdf

The list can be appended, but I think your question needs to be improved before.

share|improve this answer

answered 8 hours ago

independentvariableindependentvariable

66411 silver badge1414 bronze badges

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  The paper you cited has quite a few examples in the related work section. However they claim that "The goal of our method is not to outperform a non- learned, specialized TSP algorithm such as Concorde...". I edited my question to narrow my search for examples that do outperform non-learned algorithms.
  $endgroup$
  – klaus
  7 hours ago
  

  
  
  
  

add a comment | 

2

$begingroup$

Using OR in ML is a very popular approach due to the optimization nature lying behind ML.

However, as you ask, there are also many examples (younger, newer) where you apply ML to solve OR problems. For example, for routing problems: https://arxiv.org/pdf/1803.08475.pdf

The list can be appended, but I think your question needs to be improved before.

share|improve this answer

answered 8 hours ago

independentvariableindependentvariable

66411 silver badge1414 bronze badges

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  The paper you cited has quite a few examples in the related work section. However they claim that "The goal of our method is not to outperform a non- learned, specialized TSP algorithm such as Concorde...". I edited my question to narrow my search for examples that do outperform non-learned algorithms.
  $endgroup$
  – klaus
  7 hours ago
  

  
  
  
  

add a comment | 

$begingroup$

Using OR in ML is a very popular approach due to the optimization nature lying behind ML.

However, as you ask, there are also many examples (younger, newer) where you apply ML to solve OR problems. For example, for routing problems: https://arxiv.org/pdf/1803.08475.pdf

The list can be appended, but I think your question needs to be improved before.

share|improve this answer

answered 8 hours ago

independentvariableindependentvariable

66411 silver badge1414 bronze badges

$endgroup$

share|improve this answer

answered 8 hours ago

independentvariableindependentvariable

66411 silver badge1414 bronze badges

answered 8 hours ago

independentvariableindependentvariable

66411 silver badge1414 bronze badges

answered 8 hours ago

independentvariableindependentvariable

66411 silver badge1414 bronze badges

0

$begingroup$

There is a paper Learning Fast Optimizers for Contextual Stochastic Integer Programs where they develop a "learnable local solver" to solve problems where the MIP solvers did not scale.

I have not studied the paper, yet, but it may fit your bill.

share|improve this answer

answered 22 mins ago

Robert SchwarzRobert Schwarz

44622 silver badges77 bronze badges

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  The problems are two-stage stochastic optimization, where the learned local solver is applied to the first stage, after which the (deterministic) second stage is handed to a MIP solver. This performs better than handing the overall problem to a MIP solver (better objective within same time limit).
  $endgroup$
  – Robert Schwarz
  20 mins ago
  

  
  
  
  

add a comment | 

0

$begingroup$

There is a paper Learning Fast Optimizers for Contextual Stochastic Integer Programs where they develop a "learnable local solver" to solve problems where the MIP solvers did not scale.

I have not studied the paper, yet, but it may fit your bill.

share|improve this answer

answered 22 mins ago

Robert SchwarzRobert Schwarz

44622 silver badges77 bronze badges

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  The problems are two-stage stochastic optimization, where the learned local solver is applied to the first stage, after which the (deterministic) second stage is handed to a MIP solver. This performs better than handing the overall problem to a MIP solver (better objective within same time limit).
  $endgroup$
  – Robert Schwarz
  20 mins ago
  

  
  
  
  

add a comment | 

$begingroup$

There is a paper Learning Fast Optimizers for Contextual Stochastic Integer Programs where they develop a "learnable local solver" to solve problems where the MIP solvers did not scale.

I have not studied the paper, yet, but it may fit your bill.

share|improve this answer

answered 22 mins ago

Robert SchwarzRobert Schwarz

44622 silver badges77 bronze badges

$endgroup$

share|improve this answer

answered 22 mins ago

Robert SchwarzRobert Schwarz

44622 silver badges77 bronze badges

answered 22 mins ago

Robert SchwarzRobert Schwarz

44622 silver badges77 bronze badges

answered 22 mins ago

Robert SchwarzRobert Schwarz

44622 silver badges77 bronze badges