The L-shaped method for stochastic programs with decision-dependent uncertainty
Abstract In this paper we extend the well-known L-Shaped method to solve two-stage stochastic programming problems with decision-dependent uncertainty. The method is based on a novel, unifying, formulation and on distribution-specific optimality and feasibility cuts for both linear and integer stochastic programs. Extensive tests on three production planning problems illustrate that the method is extremely effective on large-scale instances.
Authors
- Giovanni Pantuso (ORCID: https://orcid.org/0000-0001-5028-0475)
- Mike Hewitt (ORCID: https://orcid.org/0000-0002-9786-677X)
Institutions
- University of Copenhagen (DK)
- Loyola University Chicago (US)
Publication Details
- Journal
- Mathematical Programming
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1007/s10107-025-02246-9
- Citations
- 2
- Primary Topic
- Supply Chain and Inventory Management
- Type
- article
- Field-Weighted Citation Impact
- 4.57
Funders
- Københavns Universitet
- Novo Nordisk
- Novo Nordisk Fonden