Keyword search (4,163 papers available)

"Bi H" Authored Publications:

Title Authors PubMed ID
1 Assessing the performance of a surface washing agent for oil removal from sand in cold environments Sui J; Bi H; Yue R; Fu H; Yang A; An C; 41544565
ENCS
2 Unraveling the resuspension and transformation of stranded oil: Mechanisms driving oil-particle aggregate formation in intertidal zones Yang X; Bi H; Huang G; Zhang H; Lyu L; An C; 40544777
ENCS
3 Oil spills in coastal regions of the Arctic and Subarctic: Environmental impacts, response tactics, and preparedness Bi H; Wang Z; Yue R; Sui J; Mulligan CN; Lee K; Pegau S; Chen Z; An C; 39689468
ENCS
4 Exploring the glycoprotein washing fluid-assisted cleanup for the restoration of oil-contaminated shorelines with environmental integrity Sui J; Yue R; Bi H; Fu H; Yang A; Wang M; An C; 39260515
ENCS
5 Spotlight on the vertical migration of aged microplastics in coastal waters Yang X; Huang G; Chen Z; Feng Q; An C; Lyu L; Bi H; Zhou S; 38503206
ENCS
6 Unveiling the Vertical Migration of Microplastics with Suspended Particulate Matter in the Estuarine Environment: Roles of Salinity, Particle Properties, and Hydrodynamics Yang X; Huang G; Feng Q; An C; Zhou S; Bi H; Lyu L; 38306690
ENCS
7 Towards environmentally sustainable management: A review on the generation, degradation, and recycling of polypropylene face mask waste Lyu L; Bagchi M; Markoglou N; An C; Peng H; Bi H; Yang X; Sun H; 37742382
ENCS
8 An insight into the benefits of substituting polypropylene with biodegradable polylactic acid face masks for combating environmental emissions Lyu L; Peng H; An C; Sun H; Yang X; Bi H; 37734618
ENCS
9 Assessment of the infiltration of water-in-oil emulsion into soil after spill incidents Qu Z; An C; Yue R; Bi H; Zhao S; 37414189
ENCS
10 Preparation, characteristics, and performance of the microemulsion system in the removal of oil from beach sand Bi H; Mulligan CN; Lee K; An C; Wen J; Yang X; Lyu L; Qu Z; 37399736
ENCS
11 A multi-criteria decision-making (MCDM) approach for data-driven distance learning recommendations Alshamsi AM; El-Kassabi H; Serhani MA; Bouhaddioui C; 36718426
ENCS
12 A flexible robust model for blood supply chain network design problem Khalilpourazari S; Hashemi Doulabi H; 35474752
ENCS
13 Cleanup of oiled shorelines using a dual responsive nanoclay/sodium alginate surface washing agent Yue R; An C; Ye Z; Bi H; Chen Z; Liu X; Zhang X; Lee K; 34906587
ENCS
14 Exploring the use of alginate hydrogel coating as a new initiative for emergent shoreline oiling prevention Bi H; An C; Mulligan CN; Wang Z; Zhang B; Lee K; 34346356
ENCS
15 Designing a hybrid reinforcement learning based algorithm with application in prediction of the COVID-19 pandemic in Quebec. Khalilpourazari S, Hashemi Doulabi H 33424076
ENCS
16 Investigation into the oil removal from sand using a surface washing agent under different environmental conditions. Bi H, An C, Chen X, Owens E, Lee K 32829266
ENCS

 

Title:A flexible robust model for blood supply chain network design problem
Authors:Khalilpourazari SHashemi Doulabi H
Link:pubmed.ncbi.nlm.nih.gov/35474752/
DOI:10.1007/s10479-022-04673-9
Publication:Annals of operations research
Keywords:Blood supply chainChance constraintFlexible programmingFlexible robust optimization
PMID:35474752 Category: Date Added:2022-04-27
Dept Affiliation: ENCS
1 Department of Mechanical, Industrial & Aerospace Engineering, Concordia University, Montreal, Canada.
2 Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Montreal, Canada.

Description:

World Health Organization (WHO) declared COVID-19 as a pandemic On March 12, 2020. Up to January 13, 2022, 320,944,953 cases of infection and 5,539,160 deaths have been reported worldwide. COVID-19 has negatively impacted the blood supply chain by drastically reducing blood donation. Therefore, developing models to design effective blood supply chains in emergencies is essential. This research offers a novel multi-objective Transportation-Location-Inventory-Routing (TLIR) formulation for an emergency blood supply chain network design problem. We answer questions regarding strategic, operational, and tactical decisions considering disruption in the network and blood shelf-life. Since, in real-world applications, the parameters of the proposed mathematical formulation are uncertain, two flexible uncertain models are proposed to provide risk-averse and robust solutions for the problem. We applied the proposed formulations in a case study. Under various scenarios and realizations, we show that the offered robust model handles uncertainties more efficiently and finds solutions that have significantly lower costs and delivery time. To make a reliable conclusion, we performed extensive worst-case analyses to demonstrate the robustness of the results. In the end, we provide critical managerial insights to enhance the effectiveness of the supply chain.

<strong>Supplementary information:</strong> The online version contains supplementary material available at 10.1007/s10479-022-04673-9.




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