least squares Nonlinear equation solving Multi-objective optimization Optimization Toolbox solvers are used for engineering applications in MATLAB, such...

problems with Optimization Toolbox; multiple maxima, multiple minima, and non-smooth optimization problems; estimation and optimization of model parameters...

NAG Optimization Modelling Suite. January 2024. Retrieved 25 March 2024. "Optimization Toolbox Release Notes". Mathworks Optimization Toolbox. March...

searching for zeroes. Most quasi-Newton methods used in optimization exploit this symmetry. In optimization, quasi-Newton methods (a special case of variable-metric...

and/or efficiency. Process optimization is one of the major quantitative tools in industrial decision making. When optimizing a process, the goal is to...

by using another overlaying optimizer, a concept known as meta-optimization, or even fine-tuned during the optimization, e.g., by means of fuzzy logic...

Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently...

programming (also known as mathematical optimization). More formally, linear programming is a technique for the optimization of a linear objective function, subject...

The Macintosh Toolbox implements many of the high-level features of the Classic Mac OS, including a set of application programming interfaces for software...

of solving certain mathematical optimization problems involving quadratic functions. Specifically, one seeks to optimize (minimize or maximize) a multivariate...

numerical optimization, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems...

Diffusion Toolbox): MRI analysis in Python and OpenCL MOT (Multi-threaded Optimization Toolbox): OpenCL accelerated non-linear optimization and MCMC sampling...

surrogate models: design optimization and design space approximation (also known as emulation). In surrogate model-based optimization, an initial surrogate...

solvers. In fact, it does not even require the MATLAB Optimization Toolbox. The MATLAB/DIDO toolbox does not require a "guess" to run the algorithm. This...

typecode='b', fitness=creator.FitnessMax) toolbox = base.Toolbox() toolbox.register("attr_bool", random.randint, 0, 1) toolbox.register("individual", tools.initRepeat...

freely distributable MATLAB toolbox for Kriging approximations to computer models. immoptibox: matlab toolbox for optimization and data fitting More software...

Elastix is an image registration toolbox built upon the Insight Segmentation and Registration Toolkit (ITK). It is entirely open-source and provides a...

Riedmiller. Rprop – Description and Implementation Details. Technical report, 1994 Rprop Optimization Toolbox Rprop training for Neural Networks in MATLAB...

model checker. The TLAPS proof system. The IDE is distributed in The TLA Toolbox. The TLC model checker builds a finite state model of TLA+ specifications...

of platforms and operating systems as well as a more convenient optimization toolbox. The test problems provided in CUTEr are written in Standard Input...

Euler (now Euler Mathematical Toolbox or EuMathT) is a free and open-source numerical software package. It contains a matrix language, a graphical notebook...

student David Eriksson. With this grant they built pySOT (a toolbox for surrogate global optimization) and POAP (for  asynchronous parallelism). So pySOT has...

convex optimization problems in parallel based on exchange of information among controllers. MPC is based on iterative, finite-horizon optimization of a...

Feature Selection Toolbox (FST) is software primarily for feature selection in the machine learning domain, written in C++, developed at the Institute...

which can be assessed by means of a validated questionnaire. The adaptive toolbox contains strategies for fabricating heuristic devices. The core mental...

new, recursive paradox: the decision-maker must now optimize the optimization of the optimization, and so on. Buridan's ass Decision theory Cybernetics...

of thumb. He conceptualizes rational decisions in terms of the adaptive toolbox (the repertoire of heuristics an individual or institution has) and the...

design paradigm for discrete and combinatorial optimization problems, as well as mathematical optimization. A branch-and-bound algorithm consists of a systematic...

choices, derived from parameter-fitting algorithms of the MATLAB Optimization Toolbox, for the modeling of epicardial, endocardial and myd-myocardial tissues...

simulations, numerical optimization, and modeling, simulation of explicit and implicit dynamical systems and (if the corresponding toolbox is installed) symbolic...