scholarly journals Fairness in ambulance routing for post disaster management

2021 ◽  
Author(s):  
Roberto Aringhieri ◽  
Sara Bigharaz ◽  
Davide Duma ◽  
Alberto Guastalla
Keyword(s):  
Disaster Management ◽  
General Purpose ◽  
Emergency Plans ◽  
Routing Problem ◽  
New Variant ◽  
Benchmark Instances ◽  
Neighbourhood Search ◽  
Relief Operations ◽  
Optimum Solution ◽  
Post Disaster

AbstractDisaster management generally includes the post-disaster stage, which consists of the actions taken in response to the disaster damages. These actions include the employment of emergency plans and assigned resources to (i) rescue affected people immediately, (ii) deliver personnel, medical care and equipment to the disaster area, and (iii) aid to prevent the infrastructural and environmental losses. In the response phase, humanitarian logistics directly influence the efficiency of the relief operation. Ambulances routing problem is defined as employing the optimisation tools to manage the flow of ambulances for finding the best ambulance tours to transport the injured to hospitals. Researchers pointed out the importance of equity and fairness in humanitarian relief services: managing the operations of ambulances in the immediate aftermath of a disaster must be done impartially and efficiently to rescue affected people with different priority in accordance with the restrictions. Our research aim is to find the best ambulance tours to transport the patients during a disaster in relief operations while considering fairness and equity to deliver services to patients in balance. The problem is formulated as a new variant of the team orienteering problem with hierarchical objectives to address also the efficiency issue. Due to the limitation of solving the proposed model using a general-purpose solver, we propose a new hybrid algorithm based on a machine learning and neighbourhood search. Based on a new set of realistic benchmark instances, our quantitative analysis proves that our algorithm is capable to largely reduce the solution running time especially when the complexity of the problem increases. Further, a comparison between the fair solution and the system optimum solution is also provided.

scholarly journals Advanced loading constraints for 3D vehicle routing problems

OR Spectrum ◽  
2021 ◽  
Author(s):  
Corinna Krebs ◽  
Jan Fabian Ehmke ◽  
Henriette Koch
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Comprehensive Evaluation ◽  
Time Windows ◽  
Complex Loading ◽  
Solution Quality ◽  
Routing Problem ◽  
Loading Constraints ◽  
New Variant ◽  
Neighbourhood Search

AbstractGiven automated order systems, detailed characteristics of items and vehicles enable the detailed planning of deliveries including more efficient and safer loading of distribution vehicles. Many vehicle routing approaches ignore complex loading constraints. This paper focuses on the comprehensive evaluation of loading constraints in the context of combined Capacitated Vehicle Routing Problem and 3D Loading (3L-CVRP) and its extension with time windows (3L-VRPTW). To the best of our knowledge, this paper considers the currently largest number of loading constraints meeting real-world requirements and reducing unnecessary loading efforts for both problem variants. We introduce an approach for the load bearing strength of items ensuring a realistic load distribution between items. Moreover, we provide a new variant for the robust stability constraint enabling better performance and higher stability. In addition, we consider axle weights of vehicles to prevent overloaded axles for the first time for the 3L-VRPTW. Additionally, the reachability of items, balanced loading and manual unloading of items are taken into account. All loading constraints are implemented in a deepest-bottom-left-fill algorithm, which is embedded in an outer adaptive large neighbourhood search tackling the Vehicle Routing Problem. A new set of 600 instances is created, published and used to evaluate all loading constraints in terms of solution quality and performance. The efficiency of the hybrid algorithm is evaluated by three well-known instance sets. We outperform the benchmarks for most instance sets from the literature. Detailed results and the implementation of loading constraints are published online.

Strengthening Post-Disaster Management Activities by Rating Social Media Corpus

2020 ◽  
Vol 10 (1) ◽  
pp. 34-50
Author(s):  
Banujan Kuhaneswaran ◽  
Banage T. G. S. Kumara ◽  
Incheon Paik
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Natural Disasters ◽  
Disaster Management ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Relief Operations ◽  
Post Disaster

In times of natural disasters such as floods, tsunamis, earthquakes, landslides, etc., people need information so that relief operations such as help can save many lives. The implications of using social media in post-disaster management are explored in the article. The approach has three main parts: (1) extraction, (2) classification, and (3) validation. The results prove that machine learning algorithms are highly reliable in elimination disaster non-related tweets and news posts. The authors strongly believe that their model is more reliable as they are validating the tweets using news posts by providing various ratings according to the trueness.

scholarly journals Optimization on Vehicle Routing Problem Based on Immune Clonal Selection Algorithm

2012 ◽  
Vol 6-7 ◽  
pp. 256-260
Author(s):  
Hai Hua Li ◽  
Zong Yan Xu ◽  
Fei Fei Zhou
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Clonal Selection ◽  
Solution Space ◽  
Genetic Mutation ◽  
Initial Population ◽  
Local Optimum ◽  
Clonal Selection Algorithm ◽  
Routing Problem ◽  
Optimum Solution

Vehicle routing problem is a typical NP-hard problem and is difficult to get an optimum solution. Aiming at the shortages of the existing methods, this paper proposed an algorithm based on immune clonal selection to solve vehicle routing problem. In the algorithm, expressed antibody with matrix, generated the initial population of antibodies randomly, and employed the operations such as clonal selection, genetic mutation iteratively to search optimum solution in solution space. The experimental results show that the algorithm presented here can converge to the global optimum solution rapidly, overcoming such disadvantages of the genetic algorithm as slower convergent velocity and the convergence to a local optimum solution.

A study of IoT-based post-disaster management

2017 ◽  
Author(s):  
Md Kamruzzaman ◽  
Nurul I Sarkar ◽  
Jairo Gutierrez ◽  
Sayan Kumar Ray
Keyword(s):  
Disaster Management ◽  
Post Disaster

Fred C. Cuny Memorial Continuing Education Series: Principles of Disaster Management Lesson 6: Personnel and Personnel Management

1999 ◽  
Vol 14 (4) ◽  
pp. 66-70 ◽  
Author(s):  
Fred C. Cuny
Keyword(s):  
Continuing Education ◽  
Personnel Management ◽  
Disaster Management ◽  
Relief Operations

AbstractRelief operations require capable resposible staff. This lesson discusses the types of staff and workers required. It stress the importance of employing locals an refugees infilling many of these positions and examines the role of volunteers, paid personnel, and expatriates and the issues involved.

scholarly journals The March 2021 Thessaly earthquakes and their impact through the prism of a multi-hazard approach in disaster management

2021 ◽  
Vol 58 ◽  
pp. 1
Author(s):  
Spyridon Mavroulis ◽  
Maria Mavrouli ◽  
Panayotis Carydis ◽  
Konstantinos Agorastos ◽  
Efthymis Lekkas
Keyword(s):  
Disaster Management ◽  
Good Practice ◽  
Local Population ◽  
Emergency Situation ◽  
Third Wave ◽  
Important Lesson ◽  
Affected Area ◽  
Emergency Shelters ◽  
Epidemiological Characteristics ◽  
Post Disaster

In early March 2021, when Greece was struggling with the evolving third wave of the COVID-19 pandemic with the highest numbers of daily cases and fatalities from its initiation, Thessaly was struck by a seismic sequence, which included the 3 March, Mw = 6.3 mainshock, its strongest Mw = 6.1 aftershock the following day and numerous large aftershocks. The mainshock caused extensive damage to houses and infrastructure, while the aftershock aggravated damage and caused widespread concern among residents. Based on post-event field surveys in the affected area, it is concluded that the old unreinforced houses with load-bearing masonry walls in the northeastern part of the Thessaly basin suffered the most, while the recent constructions remained intact. As a result, hundreds of homeless were in need of immediate temporary sheltering, which immediately mobilized the Civil Protection authorities to manage the emergency situation. This emergency had something unique, which made its management a challenge: the implementation of the earthquake emergency response actions was incompatible with the measures to limit the further spread of the SARS-CoV-2 virus in the community during the evolving third pandemic wave. Many of the actions have been adapted to the unprecedented conditions through a prism of a multi-hazard approach to disaster management and their impact. Among others, more and different types of emergency shelters were used to prevent overcrowding, emergency supplies distribution processes were modified to prevent transmission through hands and surfaces, places for the identification and isolation of suspected COVID-19 cases were designated in emergency shelters and extensive and regular screening testing of the local population was conducted for the detection of SARS-CoV-2 virus. From the analysis of the daily reported COVID-19 cases in the earthquake-affected area during the pre- and post- disaster periods as well as from results of rapid testing during the post-disaster period, it was found that the viral load of the earthquake-affected villages was not increased, despite the difficult and unprecedented conditions. It can be suggested that the adaptation of the measures to the new conditions has worked beneficially to reduce the spread of the new virus among those affected and the involved staff. For this reason, this approach could be considered as good practice and important lesson learned, which can be applied to similar future compound emergencies in areas with similar geoenvironmental and epidemiological characteristics.

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