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1500 questions
18
votes
3 answers
Best ways to use machine learning / AI as an OR scientist
I have come across GUROBI's webinar "Mathematical optimization and machine learning".
In essence, Mathematical Optimization (MO) and Machine Learning (ML) are different but complementary technologies. Simply put – Mixed Integer Programming (MIP)…
Kuifje
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18
votes
11 answers
Well-known parent/child pairs in the field of OR
Does the apple fall not far from the tree in operations research? Who are well-known Parent/Child pairs in operations research? I can't claim this: my father was a chemist and my son, at fifteen, has not yet caught the OR bug.
Michael Trick
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18
votes
3 answers
Small Traveling Salesman Problem instance
The Traveling Salesman Problem is perhaps the most studied of all combinatorial optimization problems. There has been a lot work in solving TSP instances to provable optimality. Concorde solves very large instances to provable optimality, with the…
Michael Trick
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18
votes
3 answers
TSP with revenue maximization
How to approach a traveling salesman problem with an aim to maximize revenue at each town visited in a certain number of days (total number of towns is greater than what can be visited in the given time window) ? The demand for the product being…
user23369
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18
votes
1 answer
Working with absolute values in constraint in a LP or MILP
Having all the approaches explained in the blog called "OR in an OB World" (this address) in my mind, I would like to ask the following question:
What is the best practice to make a constraint linear when for a variable in constraints, there is an…
Oguz Toragay
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18
votes
2 answers
What are the modern optimization methods for large systems?
I came across the preface of Optimization Theory for Large Systems (you can read it in Amazon). The author claims in the table (page v) that some of the methods such as Dantzig Wolfe decomposition, some column generations, etc. are not widely used…
Antarctica
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18
votes
3 answers
Variable fixing based on a good feasible solution
Suppose you have a combinatorial optimization problem that is formulated as a mixed integer linear program (minimization). The problem size is denoted $n$ and the expected $n$ is around $100$. The integer program has $O(n^5)$ variables and $O(n^2)$…
rasul
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18
votes
3 answers
Can an integer optimization problem be convex?
I'm trying to wrap my head around an apparent paradox that I've come across while trying to learn more about optimization algorithms:
On one hand several sources state that convex optimization is easy, because every local minimum is a global…
Skander H.
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18
votes
6 answers
Infeasibility in mathematical optimization models
Sometimes, when solving mathematical optimization models (especially MIPs), they may be infeasible. Is there any comprehensive method to deal with the infeasibility conditions? (especially in complex models)
A.Omidi
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18
votes
8 answers
Deploying OR solutions and shipping projects
My background is a bachelor in mathematics. I learned basics OR on my own using the following :
Introduction to Operations Research by F. Hillier and G. Lieberman
Integer programming by l. Wolsey
How to Solve It: Modern Heuristics by D. Fogel and…
Best_fit
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17
votes
4 answers
Where is the original Dantzig Simplex 1947 paper?
I see from here and many other sources that Dantzig invented the Simplex method in 1947. After much searching, I found that the earliest publication is this in 1956. Does anyone know where the original 1947 paper is?
jkschin
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17
votes
3 answers
As an Operations Research professional, how is your time divided when working on an optimization project?
When working on an optimization project, what is the typical time division (in percentage) between the various tasks that you have to work on:
Problem understanding/definition (figuring out what is to be
optimised, what are the relevant…
Renaud M.
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17
votes
3 answers
How Close Is Linear Programming Class to What Solvers Actually Implement for Pivot Algorithms
As part of a final project for my linear programming course, I have been asked to discuss implementations of pivot algorithms, including which combinations of the ideas we have talked about in class this fall are actually used by available solvers…
Sean Kelley
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17
votes
2 answers
Can we replace a binary variable with a continuous variable using a quadratic equality constraint?
Is it possible to replace a binary variable $x$ with a continuous variable that satisfies the quadratic equality constraint $x^2 - x=0$?
The function $f(x) = x^2 -x$ is not a convex function. Can this constraint still be helpful in using binary…
prash
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17
votes
1 answer
Family of hard instances for Gomory's cutting plane algorithm
Is there a variant of integer programs for which Gomory's cutting plane algorithm demonstrably takes a superpolynomial number of iterations?
Marcus Ritt
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