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In computer science and formal methods, a SAT solver is a computer program which aims to solve the Boolean satisfiability problem.On input a formula over Boolean variables, such as "(x or y) and (x or not y)", a SAT solver outputs whether the formula is satisfiable, meaning that there are possible values of x and y which make the formula true, or unsatisfiable, meaning that there are no such ...
[e] This is in P, since an XOR-SAT formula can also be viewed as a system of linear equations mod 2, and can be solved in cubic time by Gaussian elimination; [18] see the box for an example. This recast is based on the kinship between Boolean algebras and Boolean rings , and the fact that arithmetic modulo two forms a finite field .
In computer science and mathematical logic, satisfiability modulo theories (SMT) is the problem of determining whether a mathematical formula is satisfiable.It generalizes the Boolean satisfiability problem (SAT) to more complex formulas involving real numbers, integers, and/or various data structures such as lists, arrays, bit vectors, and strings.
The soft satisfiability problem (soft-SAT), given a set of SAT problems, asks for the maximum number of those problems which can be satisfied by any assignment. [16] The minimum satisfiability problem. The MAX-SAT problem can be extended to the case where the variables of the constraint satisfaction problem belong to the set
If the first of these two equations were equated to "=1" as usual, one could find a proof π by solving a system of linear equations (see MAX-3LIN-EQN) implying P = NP. If z ∈ L, a fraction ≥ (1 − ε) of clauses are satisfied. If z ∉ L, then for a (1/2 − ε) fraction of R, 1/4 clauses are contradicted.
The problem of Horn satisfiability is solvable in linear time. [6] A polynomial-time algorithm for Horn satisfiability is recursive: . A first termination condition is a formula in which all the clauses currently existing contain negative literals.
Mathematically, linear least squares is the problem of approximately solving an overdetermined system of linear equations A x = b, where b is not an element of the column space of the matrix A. The approximate solution is realized as an exact solution to A x = b', where b' is the projection of b onto the column space of A. The best ...
Partial Max-SAT can be solved by first considering all of the hard clauses and solving them as an instance of SAT. The total maximum (or minimum) weight of the soft clauses can be evaluated given the variable assignment necessary to satisfy the hard clauses and trying to optimize the free variables (the variables that the satisfaction of the ...
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