minimizationrearrangementsymmetricuniquenessIn this paper, we investigate two optimization problems related to a quasilinear elliptic equation with p -Laplacian, logistic-type growth rate function such that the
MAXIMIZATION AND MINIMIZATION PROBLEMS RELATED TO A $p$-LAPLACIAN EQUATION ON A MULTIPLY CONNECTED DOMAIN In this paper we investigate maximization and minimization problems related to a p-Laplacian equation on a multiply connected domain in R-2, where the admi... N Amiri,M Zivari-Rezapour - ...
Syntax is presented under the following headings: Step 1: Initialization Step 2: Definition of maximization or minimization problem Step 3: Perform optimization or perform a single function evaluation Step 4: Post, display, or obtain results Utility functions for use in all steps Definition of M ...
Our minimization problem is analogous to the one generally considered in control theory for networks18, but with the non-trivial goal of accounting for the nonlinearity characterizing Boolean dynamics. We remark that Boolean networks can be mapped to discrete-time linear dynamical systems19. However,...
7.6.6 Utility Maximization Versus Regret Minimization Conventional CL, MXL, and other models assume that respondents, in selecting an alternative in a choice set, maximize utility. Respondents may be either consumers or decision makers conserving a cultural heritage good. There is some empirical eviden...
err. sometimes stored e(opt) type of optimization always stored e(which) max or min; whether optimizer is to always stored perform maximization or minimization e(ml method) type of ml method always stored by commands using ml e(user) name of likelihood-evaluator program always stored e(...
It is simple, easy to use, and very fast. All you need to do is to define the fitness function and its variables. There are many examples of how to deal with classic genetic algorithms problems. c-plus-plus algorithm ai cpp optimization genetic-algorithm cpp14 minimization optimizer cpp11 ...
For the cardinality-constrained and unconstrained DS maximization problems, we present several deterministic algorithms and our analysis shows that the algorithms can provide provable approximation guarantees. As an application, we manage to derive an improved approximation bound for the DS minimization ...
minimisation,minimization- the act of reducing something to the least possible amount or degree or position Based on WordNet 3.0, Farlex clipart collection. © 2003-2012 Princeton University, Farlex Inc. Translations Spanish / Español Select a language: ...
In this paper, we make the first attempt on solving composite NCSC minimax problems that can have convex nonsmooth terms on both minimization and maximization variables. Our algorithm is designed based on a novel reformulation of the decentralized minimax problem that introduces a multiplier to absorb...