Real-time relief distribution in the aftermath of disasters – A rolling horizon approach

Lu, Chung-Cheng; Ying, Kuo‐Ching; Chen, Hui Ju

doi:10.1016/j.tre.2016.05.002

Cited by 75 publications

(53 citation statements)

References 40 publications

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“…In general, relief demand is dependent on various factors, including disaster type, natural environment, and even socioeconomic environment [59,60]. Some studies pile up the factors affecting the demand, which does not separate the influencing factors on the supply types and demand quantity [53,[61][62][63].…”

Section: Conceptual Frameworkmentioning

confidence: 99%

Relief Demand Calculation in Humanitarian Logistics Using Material Classification

Shao

Liang

Xi-hui

et al. 2020

IJERPH

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Demand calculation, which is the base of most logistics decisions and activities, is a critical work in humanitarian logistics (HL). However, previous studies on demand calculation in HL mainly focus on demand forecasting methodology, with many neglecting the checklist of critical supplies and practice background. This work proposes a new method for relief demand calculation by dividing the process into two parts: supply classification and demand calculation. A general method for classifying relief supplies and clarifying the checklist of relief items for multi-disaster and multiple natural scenarios is given in detail, followed by the procedure of demand calculation for each relief material. The authors present a case study to validate the feasibility and effectiveness of the proposed method based on the disaster response practice in China. Detailed lists of relief demand for different types and severities of disaster are provided.

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Section: Conceptual Frameworkmentioning

confidence: 99%

Relief Demand Calculation in Humanitarian Logistics Using Material Classification

Shao

Liang

Xi-hui

et al. 2020

IJERPH

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“…There are several goods distribution strategies in order to achieve those objectives, such as direct or multi-stop deliveries, or the use of one or several consolidation platforms in which products are consolidate to further deliveries to customers [8,22]. For the consolidation strategies it can be found several distribution networks, from which the most common are the Two tier [23,24], the Multi-layer [25] and the Four-layer city distribution network [26,27], which are depicted in figure 1. The two-tier city logistic system is based on a City Distribution Center (CDC) located on the edge of the urban zone and a set of satellites platforms that receives the goods form the CDC and deliver those to the customers using two types of vehicles, one to move the freight form CDC to satellites and other one to make the final delivery [23,.…”

Section: Urban Supply Chain (Usc) and Goods Distribution Strategiesmentioning

confidence: 99%

“…The two-tier city logistic system is based on a City Distribution Center (CDC) located on the edge of the urban zone and a set of satellites platforms that receives the goods form the CDC and deliver those to the customers using two types of vehicles, one to move the freight form CDC to satellites and other one to make the final delivery [23,. In the Multi-layer scheme, a first layer is dedicated to the suppliers, a second layer is dedicated to the CDC (or Hub) to coordinate the inbound and outbound flow of freight, and a third layer focused on the customers or the final distribution points [3,25,33,34]; The four layers' distribution strategy divided the geographic operation area into consolidation and deconsolidation zones. The first layer focused on transportation between supply points and consolidation centers (hubs), the second layer is dedicated to transport freight from hub to hub, the third layer is a deconsolidation zone at terminals or satellites facilities and the fourth layer is the delivery zone from terminals to final customers [26,27].…”

Section: Urban Supply Chain (Usc) and Goods Distribution Strategiesmentioning

confidence: 99%

An Urban Supply Chain Distribution Model

Gómez-Marín¹,

Zapata-Cortés²,

Serna³

et al. 2019

RCS

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Increased activities in urban areas related with goods transportation lead companies to look for new strategies in order to develop those process in a more efficient way, aiming to reduce costs and increase customer's satisfaction. This paper presents an urban supply chain framework and a Mixed Integer Linear Programing Model for its optimization. The model uses different goods distribution actors, including several suppliers, one consolidation facility and several customers. The proposed framework and optimization model allow to generate optimal routes and the assignment of the customers and suppliers in the distribution network.

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“…We focus on vehicle scheduling and routing for efficient pick-up and drop-off of relief materials from local warehouses to distribution points in a post-disaster setting, which is also the topic of other studies (Lu et al, 2016;Özdamar and Demir, 2012;Özdamar et al, 2004;Wang et al, 2014). Moreover, there have been studies addressing decision problems of relief distribution coupled with evacuation planning (Yi and Özdamar, 2007) and problems of pre-positioning relief materials integrated with post-disaster delivery routing (Caunhye et al, 2016;Rawls and Turnquist, 2012).…”

Section: Introductionmentioning

confidence: 99%

A column generation algorithm for vehicle scheduling and routing problems

Faiz

Vogiatzis

Noor‐E‐Alam

2019

Computers & Industrial Engineering

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During natural or anthropogenic disasters, humanitarian organizations face a series of time-sensitive tasks.One of the tasks involves picking up critical resources (e.g., first aid kits, blankets, water) from warehouses and delivering them to the affected people. To successfully deliver these items to the people in need, the organization needs to make decisions that range from the quick acquisition of vehicles from the local market, to the preparation of pickup and delivery schedules and vehicle routes. During crises, the supply of vehicles is often limited, their acquisition cost is steep, and special rental periods are imposed. At the same time, the affected area needs the aid materials as fast as possible, and deliveries must be made within due time. Therefore, it is imperative that the decisions of acquiring, scheduling, and routing of vehicles are made optimally and quickly. In this paper, we consider a variant of a truckload open vehicle routing problem with time windows, which is suitable for modeling vehicle routing operations during a humanitarian crisis.We present two integer linear programming models to formulate the problem. The first one is an arc-based mixed integer linear programming model that is solved using a general purpose solver. The second one, on the other hand, is based on a path-based formulation, for which we design a column generation framework so as to solve it. Finally, we perform numerical experiments and compare the performance of the two models. The comparison shows that the latter path-based formulation outperforms the former without sacrificing solution quality when employing our column generation framework.

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Real-time relief distribution in the aftermath of disasters – A rolling horizon approach

Cited by 75 publications

References 40 publications

Relief Demand Calculation in Humanitarian Logistics Using Material Classification

Relief Demand Calculation in Humanitarian Logistics Using Material Classification

An Urban Supply Chain Distribution Model

A column generation algorithm for vehicle scheduling and routing problems

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