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  2. Constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction

    Constraint satisfaction. In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy. [1] A solution is therefore an assignment of values to the variables that satisfies all constraints—that is, a point in ...

  3. Tabu search - Wikipedia

    en.wikipedia.org/wiki/Tabu_search

    Tabu search is a metaheuristic algorithm that can be used for solving combinatorial optimization problems (problems where an optimal ordering and selection of options is desired). Current applications of TS span the areas of resource planning, telecommunications, VLSI design, financial analysis, scheduling, space planning, energy distribution ...

  4. Complexity of constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Complexity_of_constraint...

    The complexity of constraint satisfaction is the application of computational complexity theory to constraint satisfaction. It has mainly been studied for discriminating between tractable and intractable classes of constraint satisfaction problems on finite domains. Solving a constraint satisfaction problem on a finite domain is an NP-complete ...

  5. Geometric constraint solving - Wikipedia

    en.wikipedia.org/wiki/Geometric_constraint_solving

    Geometric constraint solving is constraint satisfaction in a computational geometry setting, which has primary applications in computer aided design. A problem to be solved consists of a given set of geometric elements and a description of geometric constraints between the elements, which could be non-parametric (tangency, horizontality, coaxiality, etc) or parametric (like distance, angle ...

  6. Constraint programming - Wikipedia

    en.wikipedia.org/wiki/Constraint_programming

    Constraint programming. Constraint programming (CP) [1] is a paradigm for solving combinatorial problems that draws on a wide range of techniques from artificial intelligence, computer science, and operations research. In constraint programming, users declaratively state the constraints on the feasible solutions for a set of decision variables.

  7. Mathematical programming with equilibrium constraints

    en.wikipedia.org/wiki/Mathematical_programming...

    Mathematical programming with equilibrium constraints (MPEC) is the study of constrained optimization problems where the constraints include variational inequalities or complementarities. MPEC is related to the Stackelberg game. MPEC is used in the study of engineering design, economic equilibrium, and multilevel games.

  8. Weighted constraint satisfaction problem - Wikipedia

    en.wikipedia.org/wiki/Weighted_constraint...

    Weighted constraint satisfaction problem. In artificial intelligence and operations research, a Weighted Constraint Satisfaction Problem ( WCSP) is a generalization of a constraint satisfaction problem (CSP) where some of the constraints can be violated (according to a violation degree) and in which preferences among solutions can be expressed.

  9. Concurrent constraint logic programming - Wikipedia

    en.wikipedia.org/wiki/Concurrent_constraint...

    Concurrent constraint logic programming is a version of constraint logic programming aimed primarily at programming concurrent processes rather than (or in addition to) solving constraint satisfaction problems. Goals in constraint logic programming are evaluated concurrently; a concurrent process is therefore programmed as the evaluation of a ...