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.

An Location-Routing Problem with Simultaneous Pickup and Delivery in Urban-Rural Dual-Directions Logistics Network

2013 ◽  
Vol 756-759 ◽  
pp. 3423-3429
Author(s):  
Xue Feng Wang
Keyword(s):  
Heuristic Approach ◽  
Pickup And Delivery ◽  
Total System ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Commodity Flow ◽  
Logistics Network ◽  
Location Routing ◽  
Urban Rural ◽  
Simultaneous Pickup And Delivery

The design and optimization of urban-rural dual-directions logistics network is a substantial important issue, which will directly affect the development of the urban-rural integration in China. A reasonable scheme of logistics network will contribute to supply efficient logistics services to customers scattering in urban and rural areas. In this paper, we consider a variant of the Location-Routing-Problem (LRP), namely the LRP with simultaneous pickup and delivery in specially background (LRPSB). The objective of LRPSB is to minimize the total system cost, including depot location cost and vehicle routing cost, and implement and control the effective dual-direct commodity flow to meet customers requirement by simultaneously locating the depots and designing the vehicle routes that satisfy pickup and delivery demand of customer at the same time. A nonlinear mixed integrated programming model is formulated for the problem. Since such integrated logistics network design problems belong to a class of NP-hard problems, we propose a two-phase heuristic approach based on Tabu Search, tp-TS, to solve the large size problem and an initialization procedure to generate an initial solution for the tp-TS. We then empirically evaluate the strengths of the proposed formulations with respect to their ability to find optimal solutions or strong lower bounds, and investigate the effectiveness of the proposed heuristic approach. Computational results show that the proposed heuristic approach is computationally efficient in finding good quality solutions for the LRPSB.

scholarly journals Location-Routing Problem of Emergency Facilities under Uncertain Demand by Branch-Price and Cut

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xuchen Deng
Keyword(s):  
Demand Uncertainty ◽  
Time Window ◽  
Location Routing Problem ◽  
Protection Level ◽  
Routing Problem ◽  
Support Set ◽  
Location Routing ◽  
Robust Model ◽  
Price Cutting ◽  
Resource Constrained Shortest Path

This paper studies the location-routing problem of emergency facilities with time window under demand uncertainty. We propose a robust mathematical model in which uncertain requirements are represented by two forms: the support set defined by cardinal constraint set. When the demand value of rescue point changes in a given definition set, the model can ensure the feasibility of each line. We propose a branch and price cutting algorithm, whose pricing problem is a robust resource-constrained shortest path problem. In addition, we take the Wenchuan Earthquake as an example to verify the practicability of the method. The robust model is simulated under different uncertainty levels and distributions and compared with the scheme obtained by the deterministic problem. The results show that the robust model can run successfully and maintain its robustness, and the robust model provides better protection against demand uncertainty. In addition, we find that cost is more sensitive to uncertainty level than protection level, and our proposed model also allows controlling the robustness level of the solution by adjusting the protection level. In all experiments, the cost of robustness is that the routing cost increases by an average of 13.87%.

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.

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