Prepositioning of Emergency Supplies for Predictable Disasters Using Distributionally Robust Optimization

Jing Li; Ada Che; Feng Chu

doi:10.1016/j.ifacol.2022.10.205

Prepositioning of Emergency Supplies for Predictable Disasters Using Distributionally Robust Optimization

Jing Li, Ada Che, Feng Chu

School of Management

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

This paper examines the prepositioning of emergency supplies problem, which integrates the decisions of facility location, emergency supplies prepositioning, and distribution under predictable disasters. We scrutinize three stages of relief management in the context of predictable disasters. After that, this paper introduces a novel three-stage distributionally robust optimization (3DRO) model. To make the 3DRO model computationally tractable, we further develop a deterministic equivalent model. A real case study in China demonstrates the superiority of our proposed model.

Original language	English
Pages (from-to)	3100-3105
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	55
Issue number	10
DOIs	https://doi.org/10.1016/j.ifacol.2022.10.205
State	Published - 2022
Event	10th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2022 - Nantes, France Duration: 22 Jun 2022 → 24 Jun 2022

Keywords

disaster relief
distributionally robust optimization
facility location
inventory prepositioning
predictable disasters

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10.1016/j.ifacol.2022.10.205

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title = "Prepositioning of Emergency Supplies for Predictable Disasters Using Distributionally Robust Optimization",

abstract = "This paper examines the prepositioning of emergency supplies problem, which integrates the decisions of facility location, emergency supplies prepositioning, and distribution under predictable disasters. We scrutinize three stages of relief management in the context of predictable disasters. After that, this paper introduces a novel three-stage distributionally robust optimization (3DRO) model. To make the 3DRO model computationally tractable, we further develop a deterministic equivalent model. A real case study in China demonstrates the superiority of our proposed model.",

keywords = "disaster relief, distributionally robust optimization, facility location, inventory prepositioning, predictable disasters",

author = "Jing Li and Ada Che and Feng Chu",

note = "Publisher Copyright: Copyright {\textcopyright} 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/); 10th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2022 ; Conference date: 22-06-2022 Through 24-06-2022",

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AU - Li, Jing

AU - Che, Ada

AU - Chu, Feng

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AB - This paper examines the prepositioning of emergency supplies problem, which integrates the decisions of facility location, emergency supplies prepositioning, and distribution under predictable disasters. We scrutinize three stages of relief management in the context of predictable disasters. After that, this paper introduces a novel three-stage distributionally robust optimization (3DRO) model. To make the 3DRO model computationally tractable, we further develop a deterministic equivalent model. A real case study in China demonstrates the superiority of our proposed model.

KW - disaster relief

KW - distributionally robust optimization

KW - facility location

KW - inventory prepositioning

KW - predictable disasters

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Y2 - 22 June 2022 through 24 June 2022

ER -

Prepositioning of Emergency Supplies for Predictable Disasters Using Distributionally Robust Optimization

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Keywords

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