Stack Overflow
Stack Overflow

Questions tagged [quadratic-programming]

Quadratic programming (QP) is a special type of mathematical optimization problem. It is the problem of optimizing (minimizing or maximizing) a quadratic function of several variables subject to linear constraints on these variables.

Quadratic programming (QP) is a special type of mathematical optimization problem. It is the problem of optimizing (minimizing or maximizing) a quadratic function of several variables subject to linear constraints on these variables.

237 questions
1
vote
1 answer

When resulting in an infeasible model, what tips are there to break down the nexus of the issue

I am new to using or-tools and I have been tasked with minimizing a quadratic objective function with lots of IntVar variables. I don't know where to start breaking down what the problem could be concerning an infeasable model and welcome any tips…
Tejas
  • 11
  • 1
1
vote
2 answers

SCIP does not find good solution for MIQP problem while CPLEX finds one very quickly

I want to solve a mixed integer quadratic programming problem with 267 variables [1] using SCIP. CPLEX can solve the problem in about 30 seconds and a solution that is extremely close to the optimum is already found within a fraction of a second [2,…
Jules
  • 487
  • 3
  • 10
1
vote
0 answers

Find solution of system of quadratic inequalities

I have a system of inequalities representing the area between pairs of concentric ellipses, as seen in the following diagram: Link to the graph on desmos I want to calcualte the coordinates of the vertices of the polygon approximating the unshaded…
Jeremy
  • 661
  • 7
  • 19
1
vote
0 answers

Results view using "dykstra" R package

I use "dykstra" R package to solve my quadratic programming problem. My code is running successfully. Here it is: install.packages("Dykstra") require(Dykstra) Dmat <- diag(3) > dvec <- c(1, 1.5, 1) > Amat <- cbind(rep(1, 3), diag(3)) > bvec <- c(1,…
Nikita Rogachev
  • 11
  • 1
1
vote
2 answers

Python packages for multi-objective optimization using Successive Quadratic Programming (SQP)

Following are the characteristics of my problem: Objective function: two non-linear functions and one linear function Decision variable: two integer variables - can be relaxed as real (thus, problem can be INLP or NLP) Constraint: three (two…
vp_050
  • 583
  • 2
  • 4
  • 16
1
vote
0 answers

Solver Cosmo, how can I make a low boundary as a infinite

I'd like to compare the efficiency of solvers, so I need to optimize the same matrices with different solvers. I wonder how can I set the boundary option of the solver COSMO to inf? It worked when I type just lb=[-inf, -inf, -inf]. Is there any way…
Chiwan Park
  • 53
  • 5
1
vote
0 answers

How can I make a inf-Matrix in Julia?

I want to set up the lowest boundary of my Problem as a -inf also without a limit and here comes the codes @time begin using COSMO, SparseArrays, LinearAlgebra using NPZ Matrix10 = npzread("C:/Users/skqkr/Desktop/Semesterarbeit/Chiwan_Q1.npz") q =…
Chiwan Park
  • 53
  • 5
1
vote
0 answers

Gurobi QP solver works in an unstable way

I encountered the problem that QP solver works in an unstable way. I am solving the QP problems with the same structure at every iteration. The objective function is the same quadratic term, and each iteration I add one extra constraint to the…
Hongyu
  • 183
  • 5
1
vote
0 answers

How do I correct this Value Error due to Buffer having the wrong dimensions in a quadprog SVM implementation?

I'm using the quadprog module to set up an SVM for speech recognition. I took a QP implementation from here: https://github.com/stephane-caron/qpsolvers/blob/master/qpsolvers/quadprog_.py Here is their implementation: def quadprog_solve_qp(P, q,…
Adriaan Berger
  • 11
  • 2
1
vote
1 answer

Minimizing norm subject to linear constraint, using quadratic programming/minimization in Python

I need to solve the following quadratic minimization subject to linear inequality constraint; Where ||ξ|| is the Euclidean norm of ξ, ξ and vk are vectors and λk is a scalar. I think this can be done with CVXOPT, but I don't have any experience…
Vinzent
  • 1,070
  • 1
  • 9
  • 14
1
vote
2 answers

TypeError: argument of type 'ValueError' is not iterable in qpsolvers in python

I am new to python optimization using qpsolvers and I have problem with running the following code: import numpy as np from qpsolvers import solve_qp P = np.array([4.,5.,5.,8.]).reshape(2,2) q = np.array([-3.,2.]).reshape(1,2)[0] G =…
Erwin
  • 325
  • 1
  • 9
1
vote
1 answer

How does SLSQP uses the termination criterion parameter ftol in scipy.optimizer.minimize?

I would like to know how the SLSQP optimizer in scipy.optimizer.minimize uses the 'ftol' parameter for a problem with equality and inequality constraints? I would like to know exactly how the termination criterion is applied. Thank you in advance.
Margarida Pereira
  • 11
  • 2
1
vote
1 answer

How can I get the properties of a Gurobi's Presolve model?

I have an integer programming problem with linear objective function and some quadratic constraints. When I use Gurobi to solve this problem, Gurobi uses Presolve to create a Quadratically Constrained Integer Programming model. Now, I would like to…
jesús garcía
  • 11
  • 3
1
vote
1 answer

How to get multipliers after solving a quadratic program in ojAlgo

I implement a Sequential quadratic programming (SQP) optimizer and use ojAlgo for the quadratic programming (QP) subproblem. My question is: How do I get hold of the "Lagrange multipliers" for the QP solution? In the attached example code that solve…
Magnus
  • 35
  • 5
1
vote
0 answers

Mpmath : quadprog or lsei equivalent?

I want to solve a quadratic program with mpmath precision. The problem can be stated as a least square with linear equality and inequality constraints, or as quadratic program with linear equality and inequality constraints. I am aware of the LSEI…
lrnv
  • 1,038
  • 8
  • 19
1 2 3
…
15 16