Questions tagged [mathematical-optimization]

Mathematical optimization deals with maximizing or minimizing an objective function by choosing values from within an allowed feasible set of possible values. Mathematical optimization is often also referred to as mathematical programming or simply as optimization.

Mathematical optimization deals with maximizing or minimizing a real function by choosing values from within an allowed feasible set of possible values. Mathematical optimization is often also referred to as mathematical programming or simply as optimization.

Thus, the study of Mathematical optimization includes formulating the problem (as a set of mathematical equations), and developing several solution techniques. These techniques exploit the underlying structure of the problem. Different optimization algorithms are suited for different types of problems and vary in solution times and computational complexity.

The goal (to be maximized or minimized) is called the "Objective Function." The set of equations that limit the solution space are the "constraints" and the possible solution space is the "feasible region." In some problems, the aim is to just find any acceptable solution, and these are called "constraint satisfaction problems" in which case there is no real objective function to be minimized or maximized.

Broadly, Mathematical Optimization falls under the area of "Applied Mathematics."

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How to make cplex not output to terminal

I am using the IBM cplex optimizer to solve an optimization problem and I don't want all terminal prints that the optimizer does. Is there a member that turns this off in the IloCplex or IloModel class? These are the prints about cuts and…
DiegoNolan
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optimization function in R that can accept objective, gradient, AND hessian?

I have a complex objective function I am looking to optimize. The optimization problem takes a considerable time to optimize. Fortunately, I do have the gradient and the hessian of the function available. Is there an optimization package in R that…
Ram Ahluwalia
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Limitation of Mathematica optimization module

I have a question regarding Mathematica's global optimization capability. I came across this text related to the NAG toolbox (kind of white paper). Now I tried to solve the test case from the paper. As expected Mathematica was pretty fast in solving…
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Minimize quadratic function subject to linear equality constraints with SciPy

I have a reasonably simple constrained optimization problem but get different answers depending on how I do it. Let's get the import and a pretty print function out of the way first: import numpy as np from scipy.optimize import minimize,…
JohnE
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Need Better Algorithm for Finding Mapping Between 2 Sets of Points with Minimum Distance

Problem: I have two overlapping 2D shapes, A and B, each shape having the same number of pixels, but differing in shape. Some portion of the shapes are overlapping, and there are some pieces of each that are not overlapping. My goal is to move all…
MahlerFive
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Constraint optimisation with google operations research tools

I have a set of many (10000+) items, from which have I have to choose exactly 20 items. I can only choose each item once. My items have profits, and costs, as well as several boolean properties (such as colour). I've read and worked through the…
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how to apply gradients manually in pytorch

Starting to learn pytorch and was trying to do something very simple, trying to move a randomly initialized vector of size 5 to a target vector of value [1,2,3,4,5]. But my distance is not decreasing!! And my vector x just goes crazy. No idea what I…
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How to pack spheres in python?

I am trying to model random closed packing spheres of uniform size in a square using python. And the spheres should not overlap but I do not know how to do this I have so far: Code: import random, math, pylab def show_conf(L, sigma, title,…
altarbza
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Need help optimizing solution for Project Euler problem #12

I've been having my fun with Project Euler challenges again and I've noticed that my solution for number 12 is one of my slowest at ~593.275 ms per runthrough. This is second to my solution for number 10 at ~1254.593 ms per runthrough. All of my…
Justian Meyer
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Linear Algebra Library For Android

Does anyone know what will be a good library for computing linear algebra in Android (SVD, QR, LU, least-squares, inverse, etc) ?
James
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Why does adding Crossover to my Genetic Algorithm gives me worse results?

I have implemented a Genetic Algorithm to solve the Traveling Salesman Problem (TSP). When I use only mutation, I find better solutions than when I add in crossover. I know that normal crossover methods do not work for TSP, so I implemented both the…
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System.Math un identified

using System; using System.Math; class test { public static void Main() { Console.Write("Enter any value: "); string s=Console.ReadLine(); double n = double.Parse(s); …
Arjun
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Using CUDA to solve a system of equations in non-linear least squares fashion

Using CUDA, I would like to solve a system of equations with a non-linear least squares solver. These methods are discussed in an excellent booklet that can be downloaded here. The Jacobian matrix in my problem is sparse and lower triangular. Is…
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CVXOPT output suppression with MOSEK

I'm using the optional MOSEK solver with CVXOPT Quadratic Programming, i.e. sol = cvxopt.solvers.qp(-Q,-p,G,h,A,b,solver='mosek') Now without using the MOSEK solver, i.e. sol = cvxopt.solvers.qp(-Q,-p,G,h,A,b) Terminal output generated by CVXOPT…
Dan
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Is this solvable in polynomial (or pseudo-polynomial) time?

I'm trying to come up with a reasonable algorithm for this problem: Let's say you have a bunch of balls. Each ball has at least one color, but can also be multicolored. Each ball has a weight and a value associated with it. There are also a bunch of…