Questions tagged [optimization]

For questions involving mathematical problems that aim to minimize or maximize some objective function, possibly subject to one or more constraints.

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9
votes
3answers
264 views

To which area does constraint programming belong?

The problem I solved is a flow-shop scheduling problem with parallel machines. I solved it with the IBM ILOG CPLEX Optimization framework. There I used the constraint programming (CP). The question ...
4
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0answers
188 views

How can I formulate this multi-objective optimization problem?

Now, for each system $X$ $(X=A,B,C,E)$, my objective is $$\max\min\frac{s_{x_u}}{d_{x_u}}$$ here, $x=a$ for system A, $x=b$ for system B and follows... and for the whole system, my objective is $$\max\...
12
votes
3answers
745 views

What is a “hard problem” in the context of Mixed-integer programming?

As a practical (real-world problems) point of view, it's important we could solve optimization problems as quickly as possible (for instance, to release a daily schedule). Maybe a problem with many ...
19
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5answers
2k views

Ordered list of OR journals

Is there any compact resource that includes a list of all academic journals in the OR/MS space, ranked by journal importance? Although there are some helpful features offered by publisher websites ...
9
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1answer
186 views

Profit Maximization vs Cost Minimization for Employee Scheduling

I wanted to write two objective functions for an employee scheduling problem (MIP) until it occurred to me, that one objective function may be redundant. Is there a difference between the cost ...
10
votes
2answers
228 views

How to determine the convexity of my problem and categorize it?

My problem is: \begin{align}\min\limits_{x_{ij}}\qquad&{\sum_{i\in N}\sum_{j\in M}\frac{x_{ij}}{C_j-\sum\limits_{i\in N} x_{ij}a_i}}\\\text{s.t.}\qquad&0<C_j-\sum_{i\in N} x_{ij}a_i\\\qquad&...
10
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2answers
1k views

Infinite horizon versus finite horizon MDP

When can we approximate a finite horizon MDP with infinite horizon? Can we use infinite horizon stochastic shortest path problem on a directed acyclic graph?
11
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2answers
284 views

Decoding a Deep Neural Network as an Analytical Expression for Optimization Purpose

This post is not really about a specific question but rather a topic I am curious about to know more. We know that when it comes to integrate machine/statistical learning with optimization for the ...
6
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5answers
2k views

Algorithms vs LP or MIP

Is there a way of writing an algorithm with if-, while-statements to find an optimal solution without using linear-programming (LP)/MIP? If so, what would the benefits be against the LP/MIP? Is it ...
16
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2answers
199 views

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 ...
11
votes
1answer
264 views

Expressing a chain of boolean ORs using ILP involving different variables

How can I express a chain of OR operations in an ILP, given that each operand is an inequality between two binary variables? I have asked a similar question here: Chain of Boolean ORs. In that ...
12
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2answers
471 views

Expressing a chain of boolean ORs using ILP

How to express a chain of OR operations in an ILP in which each expression is a less than or equal constraint and the left hand side variable in all inequalities is always the same? All the variables ...
13
votes
2answers
471 views

Simulation optimisation: Monte carlo simulation, regression, optimise within regression model?

Can you help me identify if this technique has a standard name to help me explore the literature? Suppose I have a black-box stochastic simulation parameterised by $X=[x_1,...,x_p]$ with some single ...
12
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3answers
2k views

Performance of a branch and bound algorithm VS branch-cut-heuristics

I was trying to solve a moderate scheduling model using an open-source solver. I did two different ways. A) using pure branch and bound algorithm (disable all options). B) using the default setting ...
18
votes
6answers
2k views

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 ...
13
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2answers
119 views

Run repeatable numerical tests in the cloud

In numerical tests of optimization algorithms, one often reads "We used a XY computer with X GB RAM for the experiments". Usually, when I want to compare my results with theirs, I do not have an XY ...
22
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5answers
2k views

Validation and verification of mathematical models

Within the subject of simulation I have found some literature on validation and verification (e.g. Sargent's paper). My question is, what techniques do you use to validate and verify your mathematical ...
14
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7answers
856 views

What are the examples (applications) of the MIPs in which the objective function has nonzero coefficients for only continuous variables?

I'm specifically looking for real applications of the following form of MIP: $$\max\,Cx$$ subject to: \begin{align}Ax +By &= D\\Ax &= E\\By &= F\\ x &\ge 0\\ y &\in \mathbb{...
7
votes
1answer
2k views

How to linearize min function as a constraint?

I'm trying to solve an optimization problem including following constraint, and I need to linearize it in a maximization nonlinear programming model. Please help me to reformulate it with mixed ...
9
votes
1answer
158 views

Model Update for Data Driven Real Time Process Optimization

The question I am about to ask is not a technical one but rather based on following a correct approach, which I am sure would be helpful to many. I am currently working on a project which involves ...
7
votes
2answers
262 views

How to add Binary Variable with condition in LP

Notation $\text{src}_{h,s},\text{dst}_{h,s},\text{ch}_{h,s}$ are constants. $a_{h,s},x_{i,j,s}$ are binary variables. $\text{wt}_{h,s}$ are continuous variables. Problem \begin{align}\min.&\...
7
votes
2answers
508 views

How to modify EMSR when capacity for each fare class is different

In the normal EMSRa and EMSRb (Expected Marginal Seat Revenue) algorithms, each fare class is utilizes exactly 1 unit of capacity (for example, one seat on a plane). But I have a similar problem for ...
7
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2answers
760 views

Linearization of objective function

Notation $\text{src}_{h,s},\text{dst}_{h,s},\text{ch}_{h,s}$ are constants. $a_{h,s},x_{i,j,s}$ are binary variables. $\text{wt}_{h,s}$ are continuous variables. Problem \begin{align}\min.&\...
-2
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2answers
197 views

Some theories and laws of Operations Research? [closed]

Can I know some theories and laws of Operation Research which has being widely used nowadays?
9
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1answer
396 views

Finding minimum time for vehicle to reach to its destination

Given a set of Vehicles with source and destination I need to find the minimum time of travel for all the vehicles, there are also some charging stations and its necessary for vehicles to charge 1 ...
12
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3answers
287 views

Is my approach to my internship project good? Optimal allocation of product across stores, constrained optimization

Context: I am a CS student currently in a non-CS internship (logistics, supply chain). My manager wants to leverage my knowledge of programming to build a program to solve the following problem: As ...
11
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3answers
4k views

Soft constraints and hard constraints

The terms "soft constraints" and "hard constraints" are used in the context of optimization modeling. Is there any standard way to figure out which is which in some of the complicated models?
9
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2answers
344 views

What is this type of scheduling problem called?

I am currently working on software that deals with a specific type of scheduling problem, and I want to improve the scheduling algorithms that it uses. However, when I tried to research algorithms ...
6
votes
1answer
70 views

Labour Model - Resource Allocation based off Product Forecasts

at my company, we have a product level forecast that we run through a model which pulls out an hours number for our retail outlets. We do this by binning various products into categories and give ...
4
votes
1answer
423 views

Having negative value for non basic variable gives a infeasible solution in simplex method?

I try to solve the following linear program with the simplex method: $$ \begin{alignedat}{4} \max & \quad & x_1 & {}-{} & 2x_2\\ \text{subject to} & & &...
3
votes
1answer
114 views

Reduction of Unnecessary Parameters and Variables in an MIP

Let's observe an example constraint: $\sum \limits^E_{e\ \in \ A_a \ \cap \ B_b \ \cap \ C_c} x_{e,a,b,c} \geq n_{a,b,c} \; \; \; \forall a \in A,b \in B,c \in C$ with $e \in E$ an element and $A_a$ ...
15
votes
4answers
714 views

Optimization models for portfolio optimization

What are the mainstream models for portfolio optimization? We have Markowitz mean-variance model and CVaR-based models (e.g., max return subject to a CVaR constraint). What else is out there in terms ...
22
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4answers
2k views

OR-backed serious games

A "serious game" is a game (usually a simulation) designed for a primary purpose other than pure entertainment. Games like the beer game or the fresh connection can be considered serious games serving ...
1
vote
0answers
136 views

Optimal value exceeds actual value for a minimization problem [closed]

I am solving a nonlinear numerical optimization problem in Pyomo using Scip as a solver. The goal is to minimize a certain objective function. For certain input conditions, I notice that the solver ...
15
votes
3answers
327 views

Benchmark problems for scenario-based stochastic optimization

$\newcommand{\E}{\mathbb{E}}$I am working on numerical algorithms for solving convex large-scale multistage scenario-based problems and I am looking for some standard benchmarks problems. I have so ...
22
votes
4answers
4k views

What instances can be solved today by modern solvers (pure LP)?

I have found a PowerPoint presentation in which the presentor Hall claims instances could be of the size of 108 in variables and constraints to be solved today. I assume that he meant sparse problems. ...
-3
votes
1answer
86 views

Geometric interpretation of a Linear problem with bounded variables

I have a question of how to make a geometric interpretation of this problem \begin{eqnarray} \mbox{max} & z = 3x_1+x_3 \\ s.a: & \\ & \begin{array}{cc} x_1+2x_2+x_3+x_4& =...
19
votes
3answers
251 views

Variable bounds in column generation

Consider the set covering problem \[ \begin{align} \min&\ \sum_{j=1}^nc_jx_j\\ s.t.:&\ \sum_{j=1}^na_{ij}x_j\geq 1,\quad \forall i=1,\dots,m\\ &\ 0\leq x_j \leq 1 \end{align} \] ...
14
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3answers
137 views

Strategic planning based on average values

If you have strategic planning problems like hub location problems, the input data often consists of average values for shipping volumes etc. When planning capacities, it is risky to ignore the ...
10
votes
1answer
137 views

Is it possible (or straightforward) to define many secondary problems in bilevel programming?

I am new to bilevel programming. I was wondering whether it is possible (or straightforward) to formulate a bilevel problem in which there are many secondary-level problems? An example might be a ...
6
votes
1answer
64 views

Minimizing a project costs through nonlinear optimization

I have a project and I want to minimize the costs. I am are responsible for the inspection of 1000 miles of sewer grid in Canada. My goal is to provide time high quality inspection reports. I tried to ...
7
votes
1answer
352 views

KKT inequality conditions

Let's say I have an objective function $$f(x_1,x_2, \cdots, x_n)$$ and $N$ constraints $$x_i \ge 0. $$ I am trying to solve it with KKT conditions. Now the objective function becomes $$f(x_1,x_2,...
17
votes
3answers
419 views

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 ...
5
votes
1answer
267 views

Python PuLP - Unable to Model Non-Square Matrix

I am having issues with setting up constraints using both input arrays from excel and variable arrays within PuLP. It appears the model only works with square matrices and my final code has a matrix ...
19
votes
2answers
342 views

Guidelines for Linear Optimization approaches?

When solving a Linear Optimization model (or Linear Program), there are a lot of solution approaches. Just to name a few: Primal Simplex Dual Simplex Ellipsoid Method (as if) ...
13
votes
3answers
328 views

How to handle real-world (soft) constraints in an optimization problem?

Cross-posted at Stats.SE (aka Cross Validated) I am working on a problem which involves optimizing for minimum power consumption in a large compressor network interconnected through pipelines (think ...
23
votes
4answers
397 views

How to determine if a given problem seems to be a good fit to be solved using combinatorial Benders decomposition

Combinatorial Benders decomposition is a mathematical programming technique consisting into dividing a problem into a master problem and a sub problem. The master problem is solved to optimality (or ...
-8
votes
1answer
132 views

Why the optimal value that minimizes a function does not satisfy condition?

I have found a solved example of A Stochastic Two-Period Model with No Setup Cost in the book Operational Research by Hillier, 7th edition, that has a lot of complicated calculations to arrive to the ...
12
votes
1answer
597 views

Difference between lazy callbacks and using lazy constraints directly

I'm trying to use lazy constraints to solve an optimization problem. In some software such as CPLEX or GUROBI, they have some tools to handle them directly (in the original model) or using callback ...
27
votes
4answers
318 views

How to avoid having your optimization models rusting?

When designing optimization models for external organizations, I have witnessed the following: We design an optimization model for a given problem. We fine-tune it based on a portfolio of ...

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