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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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C# - Finding Peaks within a Given Width via Quadratic Fit

I'm working on an algorithm to find peaks in a List object. I'd thought up what I thought was a good (or good enough) algorithm for doing this by looking at a point and it's neighbors and, if it was a peak, adding it to the results list. However,…
JToland
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cvxpy, linear optimization, programatically build problem with objective being a sum of a few variables

I've got a problem where I need to optimize the allocation of some products. Each product has a weight (basically how much the client likes it), and a category (some clients don't accept every product) my data look something like this prod_name,…
Mohammad Athar
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Linear Programming: can I formulate an objective to maximize multiple variables at once?

Let's say I have some variables and constraints illustrated by the following system: The gray lines can stretch and shrink an amount given by the range on top of them. The blue lines are just the endpoints and show how the gray lines interact. My…
lifeformed
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Split array into sub-arrays of similar weight

I have an array of n positive numbers. I need to split it into N contiguous sub-arrays; n > N. I need to minimize [max S(j) over j] - [min S(j) over j], where S(j) denotes sum of elements in j-th sub-array, (j = 1,...,N). I.e., all sub-arrays should…
user2052436
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Algorithm: Fill different baskets

Let's assume I have 3 different baskets with a fixed capacity And n-products which provide different value for each basket -- you can only pick whole products Each product should be limited to a max amount (i.e. you can maximal pick product A 5…
Skeec
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Optimization: Oj algorithms (java) versus SCIP (python)

Does anybody know how these 2 solvers, (Oj algorithms) from Java and SCIP for Python, relate to each other performance wise (as in: which one is the fastest), when dealing with a typical MILP (Mixed Integer Linear Programming) problem? On first…
Riley
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Optimize within for loop cannot find function

I've got a function, KozakTaper, that returns the diameter of a tree trunk at a given height (DHT). There's no algebraic way to rearrange the original taper equation to return DHT at a given diameter (4 inches, for my purposes)...enter R! (using…
thatsneat
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Expressions for LPsolve

I'm working on a problem that involves constraints containing certain kind of expressions, which are to be solved using LPsolve. I can't seem to figure out how to formulate the constraints though. e.g:- I'd like to reformulate the following…
SO user
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Combinatorial constraint satisfaction and optimization

Problem I created a set of polygons based on bag of plane intersection. Now I try to create the following manifold by combinatorial optimization. Manifold constraint each edge in the final model should be incident to two polygons. Optimize weight…
Tom Hemmes
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Solving an Almost Quadratic Problem with solve.QP

I have a problem that is almost in quadratic form, but involves an extra set of vector variables. That is, I want to find the vector x that minimizes J = x' C x where C is a known positive definite matrix. The minimization is subject to the usual…
QuantRabbi
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How to extend a Loss Function Pytorch

I would like to create my own custom Loss function as a weighted combination of 3 Loss Function, something similar to: criterion = torch.nn.CrossEntropyLoss(out1, lbl1) + \ torch.nn.CrossEntropyLoss(out2, lbl2) + \ …
Chutlhu
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Efficient (e.g. vectorised) numerical solution of many parameter-sets of a low-dimensional nonlinear optimisation problem

I have a relatively simple optimisation problem of a nonlinear loss/objective function of two parameters whose algebraic solution I'm unable to find, but whose value, Jacobian and Hessian are easy to compute numerically. In fact, they are so easy to…
burnpanck
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R - finding roots for a cartesian product of function parameters

Given a function f(x,c,d) of x that also depends on some parameters c and d. I would like to find the zeroes for a cartesian product of certain values c_1,...,c_n and d_1,...,d_m of the parameters, i.e. an x_ij such that f(x_ij,c_i,d_j)=0 for…
Strickland
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Get evolution log from a pygmo archipelago

The question is pretty straightforward and maybe stupid, but here we go: as in here (https://esa.github.io/pagmo2/docs/python/algorithms/py_algorithms.html) if you evolve a single population you can get the log of your algo.evolve() call as…
Matteo
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Some Gurobi-python functions are not correctly recognized

: My problem is the following: When I use some Gurobi functions, for example quicksum() I always get the a warning like this: " 'quicksum' may be undefined, or defined from start imports: gurobipy." The following code solve the TSP…
Héctor Alonso
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