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Questions tagged [non-convex]

non-convex is a sub-set of optimisation problems domain, where a utility / penalty function does not meet a condition of convexity

In optimization, the problems for which an assumption of convex function holds over convex sets, simplifies the optimization search process in some sense, right by using the underlying convex-property, which causes the search to become, in it's way, "easier" than the general case.

problem domains do not enjoy such "ease" - for example, having both local and global minima, having inflections and similar "un-easy" properties, that may confuse or trap convex-solvers on domains.

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Polynomial goal programming (PGP) optimization examples in python

To solve linear or quadratic programming problems in python, we often resort to scipy.optimize.minimize, which provides a heuristic platform to design optimization problems. Could anyone refer me to examples of polynomial goal programming (PGP) in…
develarist
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CPLEX: Error 5002 Objective is not convex -> Problem can be solved to global optimality with optimality target 3 ->

I am receiving this error on CPLEX Optimization studio. The problem is a simple quadratic problem with one equality and two inequality constraints. .mod code shown below (no .dat used): /********************************************* * OPL…
QuentinD
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Does loss function becomes non convex when we add polynomial features?

When we use polynomial features in case of polynomial regression, logistic regression, svm , does the loss function becomes non convex ?
arjun pukale
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Python: optimize convex function over nonconvex feasible region

I'm trying to solve the following optimization problem, for data x_1, ... x_n d-dimensional vectors: where the variables are \lambda_{ij}, i=1, ... n, j = 1, ... k (real numbers) and w_1, ... w_k vectors in R^d Under the constraints for h = 2, ...…
mariob6
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CPLEX Barrier Method Iteration Limit

I am trying to solve a nonconvex-quadratic optimization problem on CPLEX, with setting optimality target to 2. Trying with different data sets I observed that the barrier method stops at the 500th iteration. I checked the settings, it is set to a…
osygl
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Optimization modelling language with support of complex variables

I am looking for optimization modelling libraries in python like CVXPY and Pyomo with support of complex variables (variables with real and imaginary part) and non-linear problems. CVXPY support complex variables but doesn't support nonlinear…
TSobhy
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Cannot evaluate constraint(s) at starting point

I am using MINLP with NEOS solver, my problem is non-convex and I get this Cannot evaluate constraint(s) at starting point what does this mean and how I can fix it?
user12036223
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Which solver can solve Fractional Linear (Costfunction) with quadratical non-convex equality constraints?

First of all, I am a noob in optimization. I have the following problem: I have the optimization vector x=(x1, x2, x3, x4, x5, x6). The cost function is: min. (x3+x4)/x6 The constraints are: - quadratically equality constraints: e.g.: k1*x5^2 +…
Cleonidas
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non-convergence of mystic optimizer

I'm trying to optimize function objective. full_constr_data consists of 6 type of goals, each goal is divided by years, each year is represented by project-based data. So, I'm weighting full_constr_data project-wise by argument x of function…
kimsergeo
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Q1 is not convex error while using decision variable in index

In my model, first I calculate the number of ports in which ship drop the cargo forall(i in 1..N,j in k+1..N) z[i][j]==sum(z in k..N-1)z*dr[i][j][z]; Then I want to use this number as the index of "t",in the form of t[z[i][j]] I'm faced with…
Hessam Soltani
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Determining concavities of a non-convex polyhedron

Suppose to have a non-convex 3D polyhedron P, expressed as a mesh. What is the best algorithm for determining the set of all its concavities? A first, maybe trivial, answer I thought could be to compute the convex hull C of the polyhedron P, and…
simonet
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How to identify all minima in a non-PSD quadratic program (QP)?

I have linearly constrained QP problems with multiple disjoint global optima (not PSD). I'd like to make a QP solver characterize all of the globally optimal solutions. Here is a very simple example of the sort of case that arises: minimize…
S. Farlies
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Difference of Convex Functions Optimization

I am looking for the method or idea to solve the following optimization problem: min f(x) s.t. g(xi, yi) <= f(x), i=1,...,n where x, y are variables in R^n. f(x) is convex function with respect to x. g(xi, yi) is a bunch of convex functions…
Zezu Liang
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Suggesting a bound for an MINLP solver

I have a mixed integer nonconvex nonlinear programming problem and it takes forever to solve. I use Couenne through pyomo and couenne is based on branching and bound. So there is algorithm guarantee on the global optimization. Basically, I used…
Jin
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Optmization of non-convex and non-concave function

I am trying to implement a profit optimization function in a cloud computing environment. Objective function is claimed to neither convex and nor concave. The function along with constraints is given as under The authors say that objective function…
sukhalid
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