Designing a humanitarian supply chain network in dynamic conditions for transferring of relief items under demand uncertainty
Mehrnaz Bathaee et al.
What the paper says
One of the challenges in crisis situations after the incident is meeting the demands of the victims. The main purpose of this article is to minimise the amount of unmet demand based on the priority of demand points. Due to the computational complexity of the problem, which is NP-hard, a super-innovative algorithm called genetic algorithm was designed to solve the real-world problem in large scale (Kermanshah earthquake in Iran) and finally the efficiency of the model was evaluated through sensitivity analysis. In addition, the results obtained from the robust approach compared to the traditional approach showed that in the best and the worst scenario, the unmet demands in the robust approach compared to the traditional approach was respectively 43% and 21% less than the traditional approach, which indicates the efficiency of the robust approach compared to the traditional approach.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.