We introduce a novel incremental network design problem motivated by the expansion of hub capacities in package express service networks: the \textit{incremental network design problem with multi-commodity flows}. We are given an initial and a target service network design, defined by a set of nodes, arcs, and origin-destination demands (commodities), and we seek to find … Read more
The European natural gas market is undergoing fundamental changes, fostering uncertainty regarding both supply and demand. This uncertainty is concentrated in the value of strategic infrastructure investments, e.g., projects of common interest supported by European Union public funds, to safeguard security of supply. This paper addresses this matter by suggesting an adaptive robust optimization framework … Read more
Online restaurant aggregators have experienced significant sales growth in recent years, driving demand for meal delivery in the US. Meal delivery logistics is quite challenging, primarily due to the difficulty in managing the supply of delivery resources to satisfy dynamic and uncertain customer demand under very tight time constraints. In this paper, we study several … Read more
We present JuDGE.jl, an open-source Julia package for solving multistage stochastic capacity expansion problems using Dantzig-Wolfe decomposition. Models for JuDGE.jl are built using JuMP, the algebraic modelling language in Julia, and solved by repeatedly applying mixed-integer programming. We illustrate JuDGE.jl by formulating and solving a toy knapsack problem, and demonstrate the performance of JuDGE.jl on … Read more
This paper addresses a general class of capacity planning problems under uncertainty, which arises, for example, in semiconductor tool purchase planning. Using a scenario tree to model the evolution of the uncertainties, we develop a multi-stage stochastic integer programming formulation for the problem. In contrast to earlier two-stage approaches, the multi-stage model allows for revision … Read more
We present a stochastic programming approach to capacity planning under demand uncertainty in semiconductor manufacturing. Given multiple demand scenarios together with associated probabilities, our aim is to arrive at a set of tools that does well across all of these scenarios. We formulate the problem as a mixed-integer program in which expected value of the … Read more