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  2. Constrained optimization - Wikipedia

    en.wikipedia.org/wiki/Constrained_optimization

    The constrained-optimization problem (COP) is a significant generalization of the classic constraint-satisfaction problem (CSP) model. [1] COP is a CSP that includes an objective function to be optimized. Many algorithms are used to handle the optimization part.

  3. Chance constrained programming - Wikipedia

    en.wikipedia.org/wiki/Chance_constrained_programming

    A general chance constrained optimization problem can be formulated as follows: (,,) (,,) =, {(,,)}Here, is the objective function, represents the equality constraints, represents the inequality constraints, represents the state variables, represents the control variables, represents the uncertain parameters, and is the confidence level.

  4. Quadratically constrained quadratic program - Wikipedia

    en.wikipedia.org/wiki/Quadratically_constrained...

    In mathematical optimization, a quadratically constrained quadratic ... is an optimization problem in which both the objective function and the ... (C++, java, .net ...

  5. Constraint programming - Wikipedia

    en.wikipedia.org/wiki/Constraint_programming

    A constraint optimization problem (COP) is a constraint satisfaction problem associated to an objective function. An optimal solution to a minimization (maximization) COP is a solution that minimizes (maximizes) the value of the objective function. During the search of the solutions of a COP, a user can wish for:

  6. Knapsack problem - Wikipedia

    en.wikipedia.org/wiki/Knapsack_problem

    A multiple constrained problem could consider both the weight and volume of the books. (Solution: if any number of each book is available, then three yellow books and three grey books; if only the shown books are available, then all except for the green book.) The knapsack problem is the following problem in combinatorial optimization:

  7. Quadratic programming - Wikipedia

    en.wikipedia.org/wiki/Quadratic_programming

    Quadratic programming (QP) is the process of solving certain mathematical optimization problems involving quadratic functions.Specifically, one seeks to optimize (minimize or maximize) a multivariate quadratic function subject to linear constraints on the variables.

  8. Optimization problem - Wikipedia

    en.wikipedia.org/wiki/Optimization_problem

    Optimization problems can be divided into two categories, depending on whether the variables are continuous or discrete: An optimization problem with discrete variables is known as a discrete optimization , in which an object such as an integer , permutation or graph must be found from a countable set .

  9. Constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction

    Constraint satisfaction toolkits are software libraries for imperative programming languages that are used to encode and solve a constraint satisfaction problem. Cassowary constraint solver, an open source project for constraint satisfaction (accessible from C, Java, Python and other languages). Comet, a commercial programming language and toolkit