2018
DOI: 10.1016/j.apm.2017.10.041
|View full text |Cite
|
Sign up to set email alerts
|

Robust optimization for relief logistics planning under uncertainties in demand and transportation time

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
28
0

Year Published

2018
2018
2023
2023

Publication Types

Select...
5
5

Relationship

0
10

Authors

Journals

citations
Cited by 87 publications
(28 citation statements)
references
References 35 publications
0
28
0
Order By: Relevance
“…This paper inspired us to consider the multistage perspective of logistics scheduling under uncertainty and to employ adjustable decisions when part of the uncertain data is realized. Recently transportation time uncertainty [7], [22] has attracted attention as a fundamental factor after a disaster. In [22], a tractable robust optimization formulation and a coaxial box uncertainty set were proposed.…”
Section: Related Workmentioning
confidence: 99%
“…This paper inspired us to consider the multistage perspective of logistics scheduling under uncertainty and to employ adjustable decisions when part of the uncertain data is realized. Recently transportation time uncertainty [7], [22] has attracted attention as a fundamental factor after a disaster. In [22], a tractable robust optimization formulation and a coaxial box uncertainty set were proposed.…”
Section: Related Workmentioning
confidence: 99%
“…is an adjusted upper bound of the right-hand side is such cases, Liu et al 2018). The increase in D i j may affect the feasibility of the problem.…”
Section: Uncertainty Of Demandsmentioning
confidence: 99%
“…It is important to understand the conceptualization of robust optimization put forth by several authors to deal with uncertainty (Laguna 1998). Robust models under polyhedral uncertainty sets have been extensively studied and implemented on linear problems (Jalilvand-Nejad et al 2016;Bertsimas and Sim 2004) and later extended to address mixed integer programming problems (Liu et al 2018). The proofs derived by Bertsimas and Sim (2004) for robust counterparts under polyhedral uncertainties cannot be generalized for non-linear mixed integer formulations.…”
Section: Literature Reviewmentioning
confidence: 99%