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  2. AC-3 algorithm - Wikipedia

    en.wikipedia.org/wiki/AC-3_algorithm

    Only the pairs (X=0, Y=4), (X=2, Y=2), and (X=4, Y=0) match the constraint C2. AC-3 then terminates, with D(X) = {0, 2, 4} and D(Y) = {0, 2, 4}. AC-3 is expressed in pseudocode as follows: Input: A set of variables X A set of domains D(x) for each variable x in X. D(x) contains vx0, vx1... vxn, the possible values of x A set of unary ...

  3. Constraint satisfaction problem - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction...

    Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables , which is solved by constraint satisfaction methods.

  4. Local consistency - Wikipedia

    en.wikipedia.org/wiki/Local_consistency

    The AC-3 algorithm improves over this algorithm by ignoring constraints that have not been modified since they were last analyzed. In particular, it works on a set of constraints that initially contains all constraints; at each step, it takes a constraint and enforces arc consistency; if this operation may have produced a violation of arc ...

  5. Three-valued logic - Wikipedia

    en.wikipedia.org/wiki/Three-valued_logic

    In fact, he did not even number the three pages of notes where he defined his three-valued operators. [3] Peirce soundly rejected the idea all propositions must be either true or false; boundary-propositions, he writes, are "at the limit between P and not P." [ 4 ] However, as confident as he was that "Triadic Logic is universally true," [ 5 ...

  6. Unit commitment problem in electrical power production

    en.wikipedia.org/wiki/Unit_Commitment_Problem_in...

    In the full AC model the complete Kirchhoff laws are used: this results in highly nonlinear and nonconvex constraints in the model. When the full AC model is used, UC actually incorporates the optimal power flow problem, which is already a nonconvex nonlinear problem.

  7. Constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction

    Constraint toolkits are a way for embedding constraints into an imperative programming language. However, they are only used as external libraries for encoding and solving problems. An approach in which constraints are integrated into an imperative programming language is taken in the Kaleidoscope programming language.

  8. Constraint logic programming - Wikipedia

    en.wikipedia.org/wiki/Constraint_logic_programming

    Constraint logic programming is a form of constraint programming, in which logic programming is extended to include concepts from constraint satisfaction. A constraint logic program is a logic program that contains constraints in the body of clauses. An example of a clause including a constraint is A (X, Y):-X + Y > 0, B (X), C (Y).

  9. Binary constraint - Wikipedia

    en.wikipedia.org/wiki/Binary_constraint

    A binary constraint, in mathematical optimization, is a constraint that involves exactly two variables. For example, consider the n-queens problem, where the goal is to place n chess queens on an n-by-n chessboard such that none of the queens can attack each other (horizontally, vertically, or diagonally). The formal set of constraints are ...