Title of article :
Multi-Objective Optimization Model for Designing a Humanitarian Logistics Network under Service Sharing and Accident Risk Concerns under Uncertainty
Author/Authors :
Mohamadi ، Salar Department of Industrial Engineering - Faculty of Industrial and Mechanical Engineering - Islamic Azad University, Qazvin Branch , Avakh Darestani ، Soroush Department of Industrial Engineering - Faculty of Industrial and Mechanical Engineering - Islamic Azad University, Qazvin Branch , Vahdani ، Behnam Department of Industrial Engineering - Faculty of Industrial and Mechanical Engineering - Islamic Azad University, Qazvin Branch , Alinezhad ، Alireza Department of Industrial Engineering - Faculty of Industrial and Mechanical Engineering - Islamic Azad University, Qazvin Branch
From page :
105
To page :
126
Abstract :
A multi-objective mathematical model is proposed to design a humanitarian logistics network under uncertain conditions. Three objective functions are considered to formulate this problem. The first one minimizes the total costs of logistics activities, the second minimizes the maximum overload of local distribution centers, and the third minimizes the maximum accident loss throughout the distribution of relief items. What is more, different simultaneous decisions are determined, including facility location-allocation, service sharing, relief distribution, truck routing, transferring service, and the evacuation of victims. Owing to the fact that the planning of humanitarian logistics problems is encountered with miscellaneous uncertain factors, such as demand, supply, costs, and capacities of facilities, a robust optimization approach is employed to tackle these challenges. Furthermore, a number of numerical instances are provided to illustrate the validity of the proposed mathematical model.
Keywords :
Humanitarian network design , Vehicle routing , Accident risk , Resource sharing , Uncertainty
Journal title :
Journal of Quality Engineering and Production Optimization
Journal title :
Journal of Quality Engineering and Production Optimization
Record number :
2696468
Link To Document :
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