Coordination of humanitarian logistic based on the quantity flexibility contract and buying in the spot market under demand uncertainty using NSGA-II and NRGA algorithms

Kord, Homeyra; Samouei, Parvaneh

doi:10.1016/j.eswa.2022.119187

Cited by 7 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After large-scale disasters, the information about the number of refugees, demand, and road conditions is generally uncertain. Many studies have considered these inseparable uncertainties to make the model close to reality [6,18,[26][27][28][29][30]. To handle the uncertainties, stochastic programming approaches are usually applied to support the decision-making process in humanitarian logistics [31].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Suppose that for a typical medical item, the supply-point category consists of eight warehouses (i.e., warehouses 1-8) that are located at Zadoi, Qumarleb, Zhidoi, Shiqu, Nangqen, Xiaosumang, Chindu, and Xiewu; the demand-point category comprises five warehouses (i.e., warehouses 9-13) that are located at Yushu (Jiegu), Shanglaxiu, Xialaxiu, Longbao, and Batang. The warehouse weights are integers generated randomly on the intervals [30,50], [20,40], and [10,30] in three periods, respectively. The simplified transportation network in disaster areas can also be identified from Ni, Shu [50].…”

Section: Case Studymentioning

confidence: 99%

See 1 more Smart Citation

Social Sustainability-Oriented Multi-Period Medical Supply Adjustment in Response to Disasters

Zhang,

Chen

2023

IEEE Access

View full text Add to dashboard Cite

Before the occurrence of disasters, medical supplies should have been prepared at warehouses to support the infected cases. As the possible mismatch between initial medical supply preparedness and actual disaster situation, it would trigger off serious social outcomes. Thus, taking medical supply adjustment operations among the warehouses is an imperative task to ensure the sustainable development of society. However, a single-period logistics action with fully uncertain information usually leads to sub-optimal schemes. In this sense, multi-period planning for medical resource adjustment is required with the concern of social sustainability, where the uncertain information is promptly adjusted following real-time cases in different periods. With the socially sustainable goals, a multi-objective stochastic optimization model is developed to facilitate the multi-period sustainable relief supply adjustment problem, which can be divided into two subproblems. The first sub-problem contains two conflicting objective functions, where a specific ε-constraint method is developed. After that, a linearization approach is applied due to the nonlinearity of the proposed model. Finally, Yushu Earthquake is considered to validate the effectiveness of the proposed model. It is found that the multi-period planning for the relief supply adjustment problem outperforms compared with a single-period one in terms of social sustainability.

show abstract