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...

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

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

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

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

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

minimizes costs like financial risk, resulting in a multi-objective optimization problem. Factors being considered may range from tangible (such as assets...

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

Shape optimization is part of the field of optimal control theory. The typical problem is to find the shape which is optimal in that it minimizes a certain...

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

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...

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

algorithms are commonly used to generate high-quality solutions to optimization and search problems via biologically inspired operators such as selection, crossover...

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

the graph. In computer science, the problem of finding a minimum vertex cover is a classical optimization problem. It is NP-hard, so it cannot be solved...

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

Multi-disciplinary design optimization (MDO) is a field of engineering that uses optimization methods to solve design problems incorporating a number of...

tree problem, or minimum Steiner tree problem, named after Jakob Steiner, is an umbrella term for a class of problems in combinatorial optimization. While...

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

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

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

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

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

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

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

routing Scheduling Problems that are decidable but not NP-complete, often are optimization problems: Knapsack optimization problems Integer programming...

are greedy algorithms that can solve this optimization problem. The heuristic method In optimization problems, heuristic algorithms find solutions close...

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