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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 ...
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.
Constraint satisfaction problem. 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 ...
Weights of propositional variables are given in the input of the problem. The weight of an assignment is the sum of weights of true variables. That problem is NP-complete (see Th. 1 of [25]). Other generalizations include satisfiability for first- and second-order logic, constraint satisfaction problems, 0-1 integer programming.
The Hungarian method is a combinatorial optimization algorithm that solves the assignment problem in polynomial time and which anticipated later primal–dual methods.It was developed and published in 1955 by Harold Kuhn, who gave it the name "Hungarian method" because the algorithm was largely based on the earlier works of two Hungarian mathematicians, Dénes Kőnig and Jenő Egerváry.
Maximum satisfiability problem. In computational complexity theory, the maximum satisfiability problem ( MAX-SAT) is the problem of determining the maximum number of clauses, of a given Boolean formula in conjunctive normal form, that can be made true by an assignment of truth values to the variables of the formula.
In computer science, a min-conflicts algorithm is a search algorithm or heuristic method to solve constraint satisfaction problems . One such algorithm is min-conflicts hill-climbing. [1] Given an initial assignment of values to all the variables of a constraint satisfaction problem (with one or more constraints not satisfied), select a ...
Local search (optimization) In computer science, local search is a heuristic method for solving computationally hard optimization problems. Local search can be used on problems that can be formulated as finding a solution that maximizes a criterion among a number of candidate solutions. Local search algorithms move from solution to solution in ...