Michel Gendreau A common assumption in the models for the vehicle routing problem with stochastic demands is that all demands must be satisfied. This is achieved by including recourse actions in two-stage stochastic programming formulations or by ensuring with a high probability that all demand fits within the vehicle capacity (chance-constrained formulations). In this work, we relax … Read more
This paper introduces the heterogeneous multicrew scheduling and routing problem (MCSRP) in road restoration. The MCSRP consists of identifying the schedule and route of heterogeneous crews that must perform the restoration of damaged nodes used in the paths to connect a source node to demand nodes in a network affected by extreme events. The objective … Read more
This paper addresses the vehicle routing problem with time windows and stochastic demands (VRPTWSD). The problem is modeled as a two-stage stochastic program with recourse, in which routes are designed in the first stage and executed in the second. A failure occurs if the load of the vehicle is insufficient to meet the observed demand … Read more
This paper proposes a multi-stage stochastic programming formulation based on affine decision rules for the reservoir management problem. Our approach seeks to find a release schedule that balances flood control and power generation objectives while considering realistic operating conditions as well as variable water head. To deal with the non-convexity introduced by the variable water … Read more
This paper proposes a multi-stage stochastic programming formulation for the reservoir management problem. Our problem specifically consists in minimizing the risk of floods over a fixed time horizon for a multi-dimensional hydro-electrical complex. We consider well-studied linear time series model and enhance the approach to consider heteroscedasticity. Using these stochastic processes under very general distributional … Read more
This paper presents a new formulation for the risk averse stochastic reservoir management problem. Using recent advances in robust optimization and stochastic programming, we propose a dynamic, multi-objective model based on minimization of a multidimensional risk measure associated with floods and droughts for a hydro-electrical complex. We present our model and then identify approximate solutions … Read more
In this paper, we propose a new approach to reduce the total running time (RT) of the progressive hedging algorithm (PHA) for solving multistage stochastic programs (MSPs) defined on a scenario tree. Instead of using the conventional scenario decomposition scheme, we apply a multi-scenario decomposition scheme and partition the scenario set in order to minimize … Read more