This paper considers the Dynamic Multi-Period Vehicle Routing Problem which deals with the distribution of orders from a depot to a set of customers over a multi-period time horizon. Customer orders and their feasible service periods are dynamically revealed over time. The objectives are to minimize total travel costs and customer waiting, and to balance the daily workload over the planning hor...

The present work investigates a Dynamic Vehicle Allocation problem (DVAP) which is faced by major forwarding companies active in road transportation. A company owning a limited fleet of vehicles wants to maximize its operational profit over an infinite horizon divided into equal periods (days). The profit stems from revenues for transporting full truckloads (FTL) and from costs derived from wai...

This paper considers the Dynamic Multi-Period Vehicle Routing Problem which deals with the distribution of orders from a depot to a set of customers over a multi-period time horizon. Customer orders and their feasible service periods are dynamically revealed over time. The objectives are to minimize total travel costs and customer waiting, and to balance the daily workload over the planning hor...

In the aftermath of a hurricane, humanitarian logistics plays critical role in delivering relief items to affected areas timely fashion. This paper proposes novel stochastic look-ahead framework that implements two-stage programming model rolling horizon approach address evolving uncertain system state during post-hurricane operations. The executes this is formulated as mixed-integer problem. a...

This paper presents an integrative methodology for managing and stabilizing the output of a wind/solar farm using storage devices in cost effective real-time manner. We consider problem where renewable should decide amount energy charged into, or withdrawn from, battery given stochastic time-varying nature power output. Our features seamless integration non-myopic decision framework sequential ...

Academic approaches considering demand uncertainty in lot sizing are seldom used practice. Industry typically implements deterministic models and accounts for uncertainties by using a rolling-horizon planning framework with frequent forecast updates. This paper bridges this gap proposing stochastic lot-sizing methodology adapted to processes. Using the martingale model of evolution (MMFE), we a...