The representation of the set of falsifying assignments of clauses via binary patterns has been useful in the design of algorithms for solving #FAL (counting the number of falsifying assignments of conjunctive forms (CF)). Given as input a CF formula F expressed by m clauses defined over n variables, we present a deterministic algorithm for computing #SAT (F ). Initially, our algorithm computes...

This paper presents a replication algorithm that implements a highly-available, non-deterministic state machine. Our algorithm generalizes the Paxos parliament algorithm of Lamport to cope with non-deterministic computations, while preserving its nice resilience and e ciency properties. The algorithm is surprisingly simple, thanks to the use of two powerful underlying abstractions: weak consens...

here in, an application of a new seismic inversion algorithm in one of iran’s oilfields is described. stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. this method integrates information from different data sources with different scales, as prior informat...

nowadays, the subject of vision metrology network design is local enhancement of the existing network. in the other words, it has changed from first to third order design concept. to improve the network, locally, some new camera stations should be added to the network in drawback areas. the accuracy of weak points is enhanced by the new images, if the related vision constraints are satisfied si...

Recently, Peña and Sohèili presented a deterministic rescaling perceptron algorithm and proved that it solves a feasible perceptron problem in O(mn log(ρ−1)) perceptron update steps, where ρ is the radius of the largest inscribed ball. The original stochastic rescaling perceptron algorithm of Dunagan and Vempala is based on systematic increase of ρ, while the proof of Peña and Sohèili is based ...

This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density function and covariance that change from period to period at random. To solve the proposed model, a novel hybrid intelligent algo...

One of the most challenging issues in multi-objective problems is finding Pareto optimal points. This paper describes an algorithm based on Benders Decomposition Algorithm (BDA) which tries to find Pareto solutions. For this aim, a multi-objective facility location allocation model is proposed. In this case, an integrated BDA and epsilon constraint method are proposed and it is shown that how P...