and economics, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization problems can be divided into...
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generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from...
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Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, where the...
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multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more...
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Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently...
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In mathematical optimization, constrained optimization (in some contexts called constraint optimization) is the process of optimizing an objective function...
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In computational science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate...
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In mathematical optimization theory, duality or the duality principle is the principle that optimization problems may be viewed from either of two perspectives...
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set of unknowns to be found using optimization. Trajectory optimization problem A special type of optimization problem where the decision variables are...
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unconstrained binary optimization (QUBO), also known as unconstrained binary quadratic programming (UBQP), is a combinatorial optimization problem with a wide...
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In machine learning, hyperparameter optimization or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter...
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operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding...
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Nonlinear programming (redirect from Nonlinear optimization)
an optimization problem where some of the constraints are not linear equalities or the objective function is not a linear function. An optimization problem...
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Genetic algorithm (redirect from Optimization using genetic algorithms)
algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation...
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Robust optimization is a field of mathematical optimization theory that deals with optimization problems in which a certain measure of robustness is sought...
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Bellman equation (redirect from Intertemporal optimization)
programming equation associated with discrete-time optimization problems. In continuous-time optimization problems, the analogous equation is a partial differential...
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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...
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Quantum optimization algorithms are quantum algorithms that are used to solve optimization problems. Mathematical optimization deals with finding the best...
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single-objective optimization cases are presented. In the second part, test functions with their respective Pareto fronts for multi-objective optimization problems (MOP)...
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answer to a particular input. Optimization problems arise naturally in many applications, such as the traveling salesman problem and many questions in linear...
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Discrete optimization is a branch of optimization in applied mathematics and computer science. As opposed to continuous optimization, some or all of the...
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Bilevel optimization is a special kind of optimization where one problem is embedded (nested) within another. The outer optimization task is commonly referred...
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been studied from various angles. Optimal facility location is an optimization problem: deciding where to place the facility in order to minimize transportation...
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the performance of the system. Topology optimization is different from shape optimization and sizing optimization in the sense that the design can attain...
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Design optimization is an engineering design methodology using a mathematical formulation of a design problem to support selection of the optimal design...
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It is an optimization problem in mathematics that arises from applications in industry. In terms of computational complexity, the problem is an NP-hard...
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NP-hard problem in combinatorial optimization, important in theoretical computer science and operations research. The travelling purchaser problem and the...
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Algorithm (redirect from Optimization algorithms)
are greedy algorithms that can solve this optimization problem. The heuristic method In optimization problems, heuristic algorithms can be used to find...
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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...
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the problem being optimized, which means DE does not require the optimization problem to be differentiable, as is required by classic optimization methods...
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