In this paper, we examine the possibility of quickly deciding whether or not an instance of a binary knapsack problem is difficult for branch and bound algorithms. We first observe that the distribution of the objective function values is smooth and unimodal. We define a measure of difficulty of...

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 probabilistic tabu search algorithm for the generalized minimum spanning tree problem. The basic idea behind the algorithm is to use preprocessing operations to arrive at a probability value for each vertex which roughly corresponds to its probability of being included...

The Traveling Salesman Problem (TSP) is one of the most widely studied problems inrncombinatorial optimization. It has long been known to be NP-hard and hence research onrndeveloping algorithms for the TSP has focused on approximate methods in addition to exactrnmethods. Tabu search is one of...

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...

The uncapacitated facility location problem is one of choosing sites among a set of candidates in which facilities can be located, so that the demands of a given set of clients are satisfied at minimum costs. Applications of neighborhood search methods to this problem have not been reported in...

Real life traveling salesman problem (TSP) instances are often large,sparse, and asymmetric. Conventional tabu search implementations for the TSP that have been reported in the literature, almost always deals with small, dense and symmetric instances. In this paper, we outline data structures...

In this paper we consider the well-known binary knapsack problem. We propose a method of embedding heuristicsi in a branch and bound framework to optain solutions with profits within a pre-specified quality parameter within very short times. Our computational experiements on the more deficult...

Conventional genetic algorithms suffer from a dependence on the initial generation used by the algorithm. In case the generation cosnsists of solutions which are not close enough to a global optimum but some of which are close to a relatively good local optimum, the algorithm is often guided a...