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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 ...
The most popular constraint propagation method is the AC-3 algorithm, which enforces arc consistency. Local search methods are incomplete satisfiability algorithms. They may find a solution of a problem, but they may fail even if the problem is satisfiable. They work by iteratively improving a complete assignment over the variables.
Jakarta EE, formerly Java Platform, Enterprise Edition (Java EE) and Java 2 Platform, Enterprise Edition (J2EE), is a set of specifications, extending Java SE [1] with specifications for enterprise features such as distributed computing and web services. [2]
JaCoP is a constraint solver for constraint satisfaction problems. It is written in Java and it is provided as a Java library. JaCoP has an interface to the MiniZinc and AMPL modeling languages. Its main focus is on ease of use, modeling power, as well as efficiency.
A constraint logic program is a logic program that contains constraints in the bodies of clauses. As an example, the clause A(X):-X>0,B(X) is a clause containing the constraint X>0 in the body. Constraints can also be present in the goal.
Node consistency requires that every unary constraint on a variable is satisfied by all values in the domain of the variable, and vice versa. This condition can be trivially enforced by reducing the domain of each variable to the values that satisfy all unary constraints on that variable.
Adding a constraint to the store is done like in regular constraint logic programming. Checking entailment of a constraint is done via guards to clauses. Guards require a syntactic extension: a clause of concurrent constraint logic programming is written as H :- G | B where G is a constraint called the guard of the clause. Roughly speaking, a ...
Cost transfer algorithms have been shown to be particularly efficient to solve real-world problem when soft constraints are binary or ternary (maximal arity of constraints in the problem is equal to 2 or 3). For soft constraints of large arity, cost transfer becomes a serious issue because the risk of combinatorial explosion has to be controlled.