In this paper we present a strategy for speeding up the estimation of expected maximum flows through reliable networks. Our strategy tries to minimize the repetition of computational effort while evaluating network states sampled using the crude Monte Carlo method. Computational experiments with...

Reliable networks are those in which network elements have a positive probability of failing. Conventional performance measures for such networks concern themselves either with expected network performance or with the performance of the network when it is performing well. In reliable networks...

The traveling salesman problem is one of the most well-solved hard combinatorial optimization problems. Any new algorithm or heuristic for the traveling salesman problem is empirically evaluated based on its performance on standard test instances, as well as on randomly generated instances....

In this paper we propose a fast state-space enumeration based algorithm called TOP-DOWN capable of computing the probability mass function of the maximum s-t flow through reliable networks. The algorithm computes the probability mass function in the decreasing order of maximum s-t flow values in...

In this paper we present a strategy for speeding up the estimation of expected maximum flows through reliable networks. Our strategy tries to minimize the repetition of computational effort while evaluating network states sampled using the crude Monte Carlo method. Computational experiments with...