Abstract: This paper considers how to increase the capacities of the elements in a set E efficiently so that probability of the total cost for the increment of capacity can be under an upper limit to maximum extent, while the final expansion capacity of a given family F of subsets of E has a given limit bound.The paper supposes the cost is a stochastic variable with some distribution.Network bottleneck capacity expansion problem with stochastic cost is originally formulated as dependent-chance programming model according to some criteria.For solving the stochastic model efficiently,network bottleneck capacity algorithm,stochastic simulation and genetic algorithm are integrated to produce a hybrid intelligent algorithm.Finally a numerical example is presented.

Key words: bottleneck capacity expansion, dependent-chance programming model, hybrid intelligent algorithm, stochastic programs