Quantum mechanics

Stochastic programming

Dynamic programming

Microeconomics

Transshipment (information security)

Fixed charge

Fixed cost

Economics

Computer science

Mathematical optimization

Transportation theory

Time horizon

Geology

Paleontology

Physics

Operations research

Mathematics

Molecular physics

Stage (stratigraphy)

Minification

Geometry

Horizon

Heuristic

Mathematical economics

Charge (physics)

Chemistry

European Journal of Operational Research

We study a fixed-charge transportation problem under stochastic and dynamic demand. We propose a multi-stage mixed integer stochastic programming formulation, where the first-stage decision is the delivery from the supplier to the retailers, while transshipment is used, in addition to classical backordering as recourse decision. The objective is the minimization of the total expected cost. We prove that this problem is NP-hard and, through a worst-case analysis, that transshipment can provide significant cost savings. Extensive computational studies are carried out to evaluate the performance of a rolling horizon approach with respect to the optimal cost. Numerical results show that this heuristic provides effective solutions in short computational time. Managerial insights are finally drawn.

A rolling horizon approach for a multi-stage stochastic fixed-charge transportation problem with transshipment