Multistage stochastic programming model and solution algorithm for the capacity expansion of railway network

Abstract

We consider a capacity expansion problem for a railway network under uncertainty. In our approach, integer and stochastic programming provide a basic framework. We develop a multistage stochastic programming model in which some of the variables are restricted to integer values. Given the distribution of the number of customers in a scenario, the problem of minimizing the expected value of the total investment cost is considered. The problem is reformulated as a problem with first stage integer variables and continuous second stage variables. An L-shaped algorithm is proposed to solve this problem.

Mitigating Investment Risk Using Modular Technologies

“…In this work, we investigate investment flexibility provided by modular technologies; to do so, we propose a multi-product capacity expansion (CE) problem that exploits the availability of technologies of different types and sizes to mitigate risk. Variants of the CE problem have been studied in different applications such as power generation, semiconductor manufacturing, railroad networks, and waste-to-energy systems [5,13,29,30]. A cost-minimization CE problem that considers a singleproduct deterministic setting with installation decisions of a fixed-capacity facility was formulated in [19].…”