Stochastic resource allocation for containerized cargo transportation networks when capacities are uncertain

• We study a stochastic resource allocation problem with random capacities.
• We formulate the problem as a stochastic programming model.
• We completely characterize the optimal solution to the model under a special network.
• We develop a sampling based algorithm to solve the model under a general network.

We consider the stochastic resource allocation problem for containerized cargo transportation with uncertain capacities and network effects, in which a freight operator needs to allocate a certain amount of capacity to each product to maximize the expected profit. We formulate the problem as a constrained stochastic programming model and provide theoretical results that completely characterize the optimal solution to the model under a special case. Under a general case, we build an approximation model of the problem and propose a sampling based algorithm to solve the approximation model. A number of numerical experiments are offered to test the algorithm.