and economics, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization problems can be divided into...

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

Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, where the...

multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more...

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

In mathematical optimization, constrained optimization (in some contexts called constraint optimization) is the process of optimizing an objective function...

In mathematical optimization theory, duality or the duality principle is the principle that optimization problems may be viewed from either of two perspectives...

operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding...

an optimization problem where some of the constraints are not linear equalities or the objective function is not a linear function. An optimization problem...

set of unknowns to be found using optimization. Trajectory optimization problem A special type of optimization problem where the decision variables are...

In machine learning, hyperparameter optimization or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter...

In computational science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate...

unconstrained binary optimization (QUBO), also known as unconstrained binary quadratic programming (UBQP), is a combinatorial optimization problem with a wide...

The knapsack problem is the following problem in combinatorial optimization: Given a set of items, each with a weight and a value, determine which items...

algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation...

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

Bilevel optimization is a special kind of optimization where one problem is embedded (nested) within another. The outer optimization task is commonly referred...

answer to a particular input. Optimization problems arise naturally in many applications, such as the traveling salesman problem and many questions in linear...

the performance of the system. Topology optimization is different from shape optimization and sizing optimization in the sense that the design can attain...

single-objective optimization cases are presented. In the second part, test functions with their respective Pareto fronts for multi-objective optimization problems (MOP)...

Quantum optimization algorithms are quantum algorithms that are used to solve optimization problems. Mathematical optimization deals with finding the best...

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

It is an optimization problem in mathematics that arises from applications in industry. In terms of computational complexity, the problem is an NP-hard...

heuristic method for solving computationally hard optimization problems. Local search can be used on problems that can be formulated as finding a solution...

NP-hard problem in combinatorial optimization, important in theoretical computer science and operations research. The travelling purchaser problem and the...

Discrete optimization is a branch of optimization in applied mathematics and computer science. As opposed to continuous optimization, some or all of the...

been studied from various angles. Optimal facility location is an optimization problem: deciding where to place the facility in order to minimize transportation...

Design optimization is an engineering design methodology using a mathematical formulation of a design problem to support selection of the optimal design...

are greedy algorithms that can solve this optimization problem. The heuristic method In optimization problems, heuristic algorithms can be used to find...

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