A new model for a 72-h post-earthquake emergency logistics location-routing problem under a random fuzzy environment

2016 ◽  
Vol 8 (5) ◽  
pp. 270-285 ◽  
Author(s):  
Jiuping Xu ◽  
Ziqi Wang ◽  
Mengxiang Zhang ◽  
Yan Tu
Keyword(s):  
Location Routing Problem ◽  
Routing Problem ◽  
New Model ◽  
Fuzzy Environment ◽  
Location Routing ◽  
Emergency Logistics

scholarly journals Research on the Model and Algorithm for Multimodal Distribution of Emergency Supplies after Earthquake in the Perspective of Fairness

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaowen Xiong ◽  
Fan Zhao ◽  
Yundou Wang ◽  
Yapeng Wang
Keyword(s):  
High Efficiency ◽  
Time Window ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Logistics Network ◽  
Emergency Rescue ◽  
Location Routing ◽  
Driving Time ◽  
Emergency Logistics ◽  
Time Window Constraints

After the earthquake, it is important to ensure the emergency supplies are provided in time. However, not only the timeliness, but also the fairness from different perspectives should be considered. Therefore, we use a multilevel location-routing problem (LPR) to study the fairness of distribution for emergency supplies after earthquake. By comprehensively considering the time window constraints, the partial road damage and dynamic recovery in emergency logistics network, the stochastic driving time of the vehicle, and the mixed load of a variety of emergency materials, we have developed a multiobjective model for the LRP in postearthquake multimodal and fair delivery of multivariety emergency supplies with a limited period. The goal of this model is to minimize the total time in delivering emergency supplies and to minimize the maximum waiting time for emergency supplies to reach demand points. A hybrid heuristic algorithm is designed to solve the model. The example shows that this algorithm has a high efficiency and can effectively realize the supply of emergency supplies after the earthquake within the specified period. This method might be particularly suitable for the emergency rescue scenarios where the victims of the earthquake are vulnerable to mood swings and the emergency supplies need to be fairly distributed.

scholarly journals The HSABA for Emergency Location-Routing Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Siliang Luan ◽  
Qingfang Yang ◽  
Huxing Zhou ◽  
Zhongtai Jiang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Bat Algorithm ◽  
Single Stage ◽  
Adaptation Mechanism ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Local Optima ◽  
Location Routing ◽  
Emergency Logistics ◽  
Nature Inspired Algorithm ◽  
Delivery Routes

This article presents a Location-Routing Problem (LRP) model to assist decision makers in emergency logistics. The model attempts to consider the relationship between the location of warehouses and the delivery routes in order to maximize the rescue efficiency. The objective function of the minimization of time and cost is established in the single-stage LRP model considering different scenarios. The hybrid self-adaptive bat algorithm (HSABA) is an improved nature-inspired algorithm for solving this LRP model, hard optimization problem. The HSABA with self-adaptation mechanism and hybridization mechanism effectively improves the defect of the original BA, that is, trapping into the local optima easily. An example is provided to prove the effectiveness of our model. The studied example shows that the single-stage LRP model can effectively select supply locations and plan rescue routes faced with different disasters and the HSABA outperforms the basic BA.

scholarly journals Optimization of Location-Routing Problem in Emergency Logistics Considering Carbon Emissions

2019 ◽  
Vol 16 (16) ◽  
pp. 2982 ◽  
Author(s):  
Shen ◽  
Tao ◽  
Shi ◽  
Qin
Keyword(s):  
Carbon Emissions ◽  
Optimal Solution ◽  
Low Carbon ◽  
Location Routing Problem ◽  
Logistics System ◽  
Routing Problem ◽  
Location Routing ◽  
Fuzzy Function ◽  
Emergency Logistics ◽  
The Government

In order to solve the optimization problem of emergency logistics system, this paper provides an environmental protection point of view and combines with the overall optimization idea of emergency logistics system, where a fuzzy low-carbon open location-routing problem (FLCOLRP) model in emergency logistics is constructed with the multi-objective function, which includes the minimum delivery time, total costs and carbon emissions. Taking into account the uncertainty of the needs of the disaster area, this article illustrates a triangular fuzzy function to gain fuzzy requirements. This model is tackled by a hybrid two-stage algorithm: Particle swarm optimization is adopted to obtain the initial optimal solution, which is further optimized by tabu search, due to its global optimization capability. The effectiveness of the proposed algorithm is verified by the classic database in LRP. What’s more, an example of a post-earthquake rescue is used in the model for acquiring reliable conclusions, and the application of the model is tested by setting different target weight values. According to these results, some constructive proposals are propounded for the government to manage emergency logistics and for the public to aware and measure environmental emergency after disasters.

Managing Emergency Material Distribution Knowledge Using Ontology-Based Modeling for Emergency Distribution Decision

2012 ◽  
Vol 605-607 ◽  
pp. 2337-2340 ◽  
Author(s):  
Li Zhang ◽  
Da Li Jiang ◽  
Ya Rong Ju ◽  
Qian Zhu Wang ◽  
Pei Pei Li
Keyword(s):  
Optimization Methods ◽  
Material Distribution ◽  
Modeling Framework ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Rule Based ◽  
Location Routing ◽  
Ontology Modeling ◽  
Ontology Model ◽  
Emergency Logistics

Aiming at the knowledge representation problem in emergency logistics, this paper presents an ontology-based modeling framework for emergency distribution decision. The suggested ontology model includes the meta-ontology, the domain ontology and the upper relationship, and it can be extended to meet the various requirements in emergency logistics application. As an illustrative example, an instance of Location Routing Problem (LRP) is defined using proposed ontology model, and a rule-based reasoning experiment is developed with Jena. The result of experiment demonstrates the effectiveness of the ontology modeling framework, which can be used as an important complement to traditional optimization methods for emergency distribution decision.

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