Priority-Index Based Multi-Priority Relief Logistics Scheduling with Greedy Heuristic Search

被引:0
|
作者
Mishra, Bhupesh Kumar [1 ]
Adhikari, Tek Narayan [2 ]
Dahal, Keshav [1 ]
Pervez, Zeeshan [1 ]
机构
[1] Univ West Scotland, Sch Engn & Comp, Artificial Intelligence Visual Commun & Networks, Paisley, Renfrew, Scotland
[2] Kantipur Engn Coll, Dept Comp & Elctron Engn, Patan, Nepal
基金
“创新英国”项目;
关键词
Rational distribution; Priority; Disaster; Greedy Heuristic Search; Scheduling; Relief logistics; DISASTER RELIEF; GENETIC ALGORITHM;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Spontaneous response after any kind of disaster is essential to rescue victims at the disaster-affected regions. Efficient and effective relief logistics scheduling is crucial to reduce the disaster impact on the people in the affected areas. Such scheduling plan remains challenging in the field of relief logistics and related study areas because of the constraints such as time, cost, priorities and limited resources. Also, the nature of requirements of victims changes dynamically that makes the scheduling task more challenging. This leads to formulate a distinctive relief logistics scheduling covering disaster regions requirement and priorities. With the limited availability of the vehicles, the scheduling needs to be planned in iterative manner with the multiple time slots based on the availability of the vehicles. A greedy heuristic with priority based search generates the optimal set of scheduling sequences in the iterative time-slot scenarios. Covering priority aspect gives an effective alternative for the rational scheduling of the relief logistics. In this paper, we focus especially on an optimal weighted priority relief logistics scheduling model based on different priorities with least dependency on the choice of scheduling sequence. The resulting model is appropriate for relief logistics scheduling in the early phase of disaster response. The simulated result shows that the weighted priority relief logistics scheduling model generates comparatively better scheduling schedule in comparison with sequences generated by applying the priorities individually.
引用
收藏
页数:8
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