In transportation problems and in many other planning problems, there are important sources of uncertainty that must be addressed to find effective and efficient solutions. A common approach for solving these dynamic and stochastic problems is the Multiple Scenario Approach (MSA), that has been proved effective for transportation problems, but it does not provide flexibility … Read more
We focus on a problem of locating recharging stations in one-way station based electric car sharing systems which operate under demand uncertainty. We model this problem as a mixed integer stochastic program and develop a Benders decomposition algorithm based on this formulation. We integrate a stabilization procedure to our algorithm and conduct a large-scale experimental … Read more
We present a new primal-dual algorithm for computing the value of the Lagrangian dual of a stochastic mixed-integer program (SMIP) formed by relaxing its nonanticipativity constraints. The algorithm relies on the well-known progressive hedging method, but unlike previous progressive hedging approaches for SMIP, our algorithm can be shown to converge to the optimal Lagrangian dual … Read more