example a function or the shape of a body. Such a problem is an infinite-dimensional optimization problem, because, a continuous quantity cannot be determined...

such as those shown above are frequently associated with infinite-dimensional optimization problems with constraints. For example, the Stokes equations...

optimal control problem modelling advertising Infinite-dimensional optimization Semi-infinite programming — infinite number of variables and finite number of...

Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute...

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...

of optimization methods that sample from a hypersphere surrounding the current position. Random optimization is a related family of optimization methods...

possible. Local search is a sub-field of: Metaheuristics Stochastic optimization Optimization Fields within local search include: Hill climbing Simulated annealing...

generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from...

solution. Shape optimization is an infinite-dimensional optimization problem. Furthermore, the space of allowable shapes over which the optimization is performed...

Robust optimization is a field of mathematical optimization theory that deals with optimization problems in which a certain measure of robustness is sought...

Random optimization (RO) is a family of numerical optimization methods that do not require the gradient of the problem to be optimized and RO can hence...

problem being optimized, which means DE does not require the optimization problem to be differentiable, as is required by classic optimization methods such...

trajectory optimization were in the aerospace industry, computing rocket and missile launch trajectories. More recently, trajectory optimization has also...

problems containing variables with infinite domain. These are typically solved as optimization problems in which the optimized function is the number of violated...

Specifically, it is a metaheuristic to approximate global optimization in a large search space for an optimization problem. For large numbers of local optima, SA...

strategy for numerical optimization. Evolution strategies (ES) are stochastic, derivative-free methods for numerical optimization of non-linear or non-convex...

from a randomly selected subset of the data). Especially in high-dimensional optimization problems this reduces the very high computational burden, achieving...

In the field of mathematical optimization, stochastic programming is a framework for modeling optimization problems that involve uncertainty. A stochastic...

programming equation (DPE) associated with discrete-time optimization problems. In continuous-time optimization problems, the analogous equation is a partial differential...

on flexible structures, smart materials, hysteresis, and infinite-dimensional optimization. She is a professor at the University of Waterloo, the former...

space is finite-dimensional if its dimension is a natural number. Otherwise, it is infinite-dimensional, and its dimension is an infinite cardinal. Finite-dimensional...

method (see the Kantorovich theorem). Kantorovich considered infinite-dimensional optimization problems, such as the Kantorovich-Monge problem in transport...

In mathematical optimization, fractional programming is a generalization of linear-fractional programming. The objective function in a fractional program...

calculus to be generalized from (finite-dimensional) Euclidean vector spaces to spaces that may be infinite-dimensional. Hilbert spaces arise naturally and...

search (RS) is a family of numerical optimization methods that do not require the gradient of the problem to be optimized, and RS can hence be used on functions...

In optimization theory, semi-infinite programming (SIP) is an optimization problem with a finite number of variables and an infinite number of constraints...

people are given: A container, usually a two- or three-dimensional convex region, possibly of infinite size. Multiple containers may be given depending on...

Variational bicomplex Fermat's principle Principle of least action Infinite-dimensional optimization Finite element method Functional analysis Ekeland's variational...

to the power of three (the conventional dimension of the filled sphere). However, if a fractal's one-dimensional lengths are all doubled, the spatial content...

for two-dimensional Euclidean geometry). Euclid sometimes distinguished explicitly between "finite lines" (e.g., Postulate 2) and "infinite lines" (book...