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Main Authors: Hu, Haitao, Li, Jing, Tang, Jiafu, Zeng, Bo
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.21225
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author Hu, Haitao
Li, Jing
Tang, Jiafu
Zeng, Bo
author_facet Hu, Haitao
Li, Jing
Tang, Jiafu
Zeng, Bo
contents The bilevel facility location problem (BO-FLP) is one of the core optimization problems behind the design of many decentralized industrial systems, e.g., supply chain systems where a supplier constructs some critical facilities and then uses them to serve retailers in a cost-effective fashion, while retailers directly handle customers aiming to minimize the total unmet demand in a rather independent fashion. When uncertainty is considered, scenario-based stochastic approaches are commonly used, but they often become impractical due to insufficient data or an exponential number of scenarios. To address this issue, this paper adopts robust optimization and proposes a novel two-stage robust bilevel facility location model. Several structural properties are derived to improve both theoretical understanding and solution efficiency. Based on this, an enhanced column-and-constraint generation algorithm is developed for robust bilevel optimization with decision-dependent uncertainty, significantly improving exact solution capability over the standard method. Numerical results show that, compared to the centralized two-stage RO model, our model pays more attention to demand fulfillment, typically resulting in higher service efficiency and better utilization of supply capacity. Under a small-scale disruption, this new model delivers better service performance. However, under a large-scale disruption, the centralized model performs more effectively.
format Preprint
id arxiv_https___arxiv_org_abs_2603_21225
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Two-stage robust bilevel optimization model for facility location considering operational service level under disruption risk
Hu, Haitao
Li, Jing
Tang, Jiafu
Zeng, Bo
Optimization and Control
The bilevel facility location problem (BO-FLP) is one of the core optimization problems behind the design of many decentralized industrial systems, e.g., supply chain systems where a supplier constructs some critical facilities and then uses them to serve retailers in a cost-effective fashion, while retailers directly handle customers aiming to minimize the total unmet demand in a rather independent fashion. When uncertainty is considered, scenario-based stochastic approaches are commonly used, but they often become impractical due to insufficient data or an exponential number of scenarios. To address this issue, this paper adopts robust optimization and proposes a novel two-stage robust bilevel facility location model. Several structural properties are derived to improve both theoretical understanding and solution efficiency. Based on this, an enhanced column-and-constraint generation algorithm is developed for robust bilevel optimization with decision-dependent uncertainty, significantly improving exact solution capability over the standard method. Numerical results show that, compared to the centralized two-stage RO model, our model pays more attention to demand fulfillment, typically resulting in higher service efficiency and better utilization of supply capacity. Under a small-scale disruption, this new model delivers better service performance. However, under a large-scale disruption, the centralized model performs more effectively.
title Two-stage robust bilevel optimization model for facility location considering operational service level under disruption risk
topic Optimization and Control
url https://arxiv.org/abs/2603.21225