generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from...
52 KB (6,012 words) - 10:08, 25 August 2024
convex optimization problems admit polynomial-time algorithms, whereas mathematical optimization is in general NP-hard. A convex optimization problem...
30 KB (3,097 words) - 23:17, 1 July 2024
Continuous optimization is a branch of optimization in applied mathematics. As opposed to discrete optimization, the variables used in the objective function...
1 KB (93 words) - 23:03, 28 November 2021
Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, where the...
18 KB (1,822 words) - 00:11, 9 June 2024
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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transformation between input and output values, described by a mathematical function, optimization deals with generating and selecting the best solution from...
14 KB (1,243 words) - 21:03, 16 August 2024
Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute...
74 KB (9,564 words) - 04:04, 27 August 2024
In mathematical optimization, constrained optimization (in some contexts called constraint optimization) is the process of optimizing an objective function...
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hyperparameter optimization methods. Bayesian optimization is a global optimization method for noisy black-box functions. Applied to hyperparameter optimization, Bayesian...
23 KB (2,457 words) - 22:19, 7 August 2024
Bilevel optimization is a special kind of optimization where one problem is embedded (nested) within another. The outer optimization task is commonly referred...
14 KB (2,183 words) - 05:52, 20 June 2024
Robust optimization is a field of mathematical optimization theory that deals with optimization problems in which a certain measure of robustness is sought...
23 KB (3,399 words) - 15:13, 25 August 2024
researchers active in optimization. The MOS encourages the research, development, and use of optimization—including mathematical theory, software implementation...
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(often referred to as simply, “Gurobi”) is a solver, since it uses mathematical optimization to calculate the answer to a problem. Gurobi is included in the...
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Topology optimization is a mathematical method that optimizes material layout within a given design space, for a given set of loads, boundary conditions...
23 KB (2,492 words) - 17:04, 26 April 2024
when the function is at most linear. Linear algebra Mathematical optimization Convex optimization Linear programming Quadratic programming Scientific...
5 KB (553 words) - 02:54, 11 June 2024
Topological optimization techniques can then help work around the limitations of pure shape optimization. Mathematically, shape optimization can be posed...
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Derivative-free optimization (sometimes referred to as blackbox optimization) is a discipline in mathematical optimization that does not use derivative...
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must be estimated for each technology. In mathematics, mathematical optimization (or optimization or mathematical programming) refers to the selection of...
134 KB (13,620 words) - 21:44, 28 July 2024
Discrete optimization is a branch of optimization in applied mathematics and computer science. As opposed to continuous optimization, some or all of the...
2 KB (174 words) - 15:49, 12 July 2024
Multi-disciplinary design optimization (MDO) is a field of engineering that uses optimization methods to solve design problems incorporating a number...
22 KB (2,878 words) - 14:16, 12 July 2024
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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Quadratic programming (category Optimization algorithms and methods)
process of solving certain mathematical optimization problems involving quadratic functions. Specifically, one seeks to optimize (minimize or maximize) a...
22 KB (1,910 words) - 19:14, 13 August 2024
Mathematical finance, also known as quantitative finance and financial mathematics, is a field of applied mathematics, concerned with mathematical modeling...
23 KB (2,426 words) - 21:17, 30 May 2024
developing a mathematical model is termed mathematical modeling. Mathematical models are used in applied mathematics and in the natural sciences (such as physics...
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has several patents awarded. He has worked machine learning and mathematical optimization, and more recently on control theory and reinforcement learning...
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Simulation-based optimization (also known as simply simulation optimization) integrates optimization techniques into simulation modeling and analysis...
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Dynamic programming (redirect from Dynamic optimization)
Dynamic programming is both a mathematical optimization method and an algorithmic paradigm. The method was developed by Richard Bellman in the 1950s and...
61 KB (9,265 words) - 17:23, 3 August 2024
computational complexity and optimization the no free lunch theorem is a result that states that for certain types of mathematical problems, the computational...
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Quasiconvex function (category Convex optimization)
have applications in mathematical analysis, in mathematical optimization, and in game theory and economics. In nonlinear optimization, quasiconvex programming...
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Hill climbing (redirect from Hill-climbing optimization)
In numerical analysis, hill climbing is a mathematical optimization technique which belongs to the family of local search. It is an iterative algorithm...
12 KB (1,549 words) - 16:36, 8 August 2024