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.

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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

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article

The L-shaped method for stochastic programs with decision-dependent uncertainty

Giovanni Pantuso, Mike Hewitt
2 citations
Mathematical Programming
Supply Chain and Inventory Management
4.57
article

The L-shaped method for stochastic programs with decision-dependent uncertainty

Giovanni Pantuso, Mike Hewitt
article en
2 citations

Abstract

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.

Mathematical Programming
University of Copenhagen (DK), Loyola University Chicago (US)
Københavns Universitet, Novo Nordisk, Novo Nordisk Fonden
Openalex Percentile: Top 6%
Supply Chain and Inventory Management
4.57
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