Approximating Solution Probabilities in CSPs

Bayes Networks for Estimating the Number of Solutions to a CSP

The problem of counting the number of solutions to a constraint satisfaction problem (CSP) is rephrased in terms of probability updating in Bayes networks. Approximating the probabilities in Bayes networks is a problem which has been studied for a while, and may well provide a good approximation to counting the number of solutions. We use a simple approximation based on independence, and show t...

Approximating solution of fully fuzzy linear systems in dual form

Approximating CSPs with global cardinality constraints using SDP hierarchies

This work is concerned with approximating constraint satisfaction problems (CSPs) with an additional global cardinality constraints. For example, Max Cut is a boolean CSP where the input is a graph G = (V, E) and the goal is to find a cut S ∪ S̄ = V that maximizes the number of crossing edges, |E(S , S̄ )|. The Max Bisection problem is a variant of Max Cut with an additional global constraint tha...

Histogram Arc Consistency as a Value Ordering Heuristic

The Constraint Satisfaction Problem (CSP:I is NP-hard. Finding solutions requires searching in an exponential space of possible variable assignments. Good value ordering heuristics are essential for finding solutions to CSPs. Such heuristics estimate the probability that any particular variable assignment will appear in a globally consistent solution. Unfortunately, computing solution probabili...

A New Approach for Approximating Solution of Continuous Semi-Infinite Linear Programming

‎This paper describes a new optimization method for solving continuous semi-infinite linear problems‎. ‎With regard to the dual properties‎, ‎the problem is presented as a measure theoretical optimization problem‎, ‎in which the existence of the solution is guaranteed‎. ‎Then‎, ‎on the basis of the atomic measure properties‎, ‎a computation method was presented for obtaining the near optimal so...