generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from...
51 KB (5,907 words) - 03:41, 31 May 2024
convex optimization problems admit polynomial-time algorithms, whereas mathematical optimization is in general NP-hard. A convex optimization problem...
30 KB (3,092 words) - 15:23, 10 April 2024
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 (1,877 words) - 03:16, 3 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...
27 KB (3,869 words) - 02:21, 15 April 2024
researchers active in optimization. The MOS encourages the research, development, and use of optimization—including mathematical theory, software implementation...
4 KB (396 words) - 00:14, 25 April 2024
Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute...
74 KB (9,512 words) - 18:44, 16 May 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
hyperparameter optimization methods. Bayesian optimization is a global optimization method for noisy black-box functions. Applied to hyperparameter optimization, Bayesian...
23 KB (2,460 words) - 16:35, 4 January 2024
(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...
6 KB (478 words) - 23:49, 4 March 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 (2,174 words) - 06:11, 20 April 2024