A multi-organisational approach for disaster preparedness and response:the use of optimisation and GIS for facility location, stock pre-positioning, resource allocation and relief distribution

From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management

Can 3D Printing address operations challenges in Disaster Management?

Disaster management entails activities for responding to and recovering from disruption to normal conditions. Disasters restrict the ability of operations managers, but technologies such as 3D printing have been proposed as a means of overcoming some of the restrictions. This research uses a state-of-the-art review of 3D printing technologies to determine the current and future potential to meet disaster management challenges. Specifically, one of the main categories of items listed in the Sphere Project handbook is considered. The analysis evaluates short, medium and long term feasibility and provides a research agenda for 3D printing and disaster management

Disaster preparedness in humanitarian logistics:A collaborative approach for resource management in floods

The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency. Consequently, successful operations rely heavily on the collaboration of different organisations. Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence. This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities. The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities

Stock Prepositioning For Disasters In Mexico: A Case

Different governments are recurring to stock prepositioning to improve immediate disaster response because it can reduce procurement delays and distribution lead-time. However, it can be an expensive policy. Mexico has used this policy for several years with poor results. The purpose of this research is to integrate GIS and optimisation for the analysis of the location of warehousing facilities and prepositioning of stock at a national level. The system was tested using data obtained from Mexican disaster authorities and compared to the current policy, showing better coverage in terms of quality and a reduction of shipment time for several areas

Decision-making and operations in disasters: challenges and opportunities

Decision-making structures are commonly associated with the logistics challenges experienced during disaster operations. However, the alignment between the operational level and the decision-making structure is commonly overlooked. The purpose of this research is to provide an analysis of the fit of both levels and its impact on performance. The research is developed around a case study in Mexico. Through a review of the disaster management policy in the country, interviews, and secondary data, the article provides an analysis of the current decision-making structure, the logistics activities undertaken by authorities and the impact of the alignment between both components on logistics performance. The analysis suggests that several of the challenges commonly associated centralisation are actually rooted on its alignment with the operational level. Logistics performance is negatively affected by faulty assumptions, poorly planned procedures, inconsistent decision-making, and poorly designed structures. The case showed the need to align the operational level with a centralised perspective to increase responsiveness, flexibility and the interaction between different organisations. This article identifies the impact of the misalignment between the decision-making structure and the operational level on logistics performance, an area currently understudied. It moves from the current argument about the appropriate decision-making structure for disaster management to the identification of components to implement an efficient and effective disaster management system. Additionally, this paper provides recommendations for best practices in humanitarian logistics which are applicable to Mexico and other countries using a centralised decision-making approach

If Blockchain is the answer what is the question?

The purpose of the paper is to identify the issues and challenges to employing blockchain technology for different operations context. The paper analyses five cases to identify drivers and barriers to adopting the technology. Our findings suggest that interoperability and platform dependency can limit the wide-scale deployment of the technology. Additionally, trust in rule-based software automation and consensus among supply chain actors can inhibit effective adoption. In summary, the paper finds that care should be taken when applying blockchain, since there are many situations where its implementation is not feasible or not beneficial

Understanding Value of Social Media in Supply Chain Management

The purpose of the paper is to extend the social media analytics frameworks reported in the existing literature to create value from the data captured from heterogenous social media and IoT sources in a global supply-chain. The paper will aid the practitioners to understand the importance of focussed analysis and the key requirements for this analysis by offering a guide to organisational needs. The framework and requirements proposed in the paper will aid managers to capture value from the data (i.e. gain key insights) and augment human decision-making

Sustainability and intermodality in humanitarian logistics: A two-stage multi-objective programming formulation

When managing crises and disasters, decision-makers face high uncertainty levels, disrupted supply chains, and damaged infrastructure. This complicates delivering resources that are essential for the survival of the victims. Flexible and adaptable supply networks are needed to ensure a consistent flow of relief to the areas affected by disasters. Intermodality is a valuable approach when infrastructure is damaged, as it allows the use of different delivery modes to reach demand areas. Nevertheless, involving different transportation modes has an impact on the environment. Looking at the importance of helping victims and considering the environmental impact of humanitarian operations for long-term sustainability, intermodality and carbon emission reduction measures can be an interesting combination. This area, however, is currently understudied. This article introduces a two-stage stochastic formulation to fill that gap. The model addresses facility location, resource allocation, and intermodal relief distribution considering carbon emission reduction in facilities, intermodal activities, and distribution. The formulation minimises costs and the level of shortage of relief. The model is tested using a case study in Sinaloa, Mexico, to investigate the impact of intermodality and carbon emission reduction measures on costs and shortage of relief for disaster victims. The findings confirm that the model proposed allows for the diversification of transportation modes and reduces carbon emissions whilst achieving a good level of performance in both metrics. The comparison with a benchmark model without intermodality and carbon reduction measures suggests that the formulation can increase flexibility and reduce the level of CO2 emissions whilst maintaining high satisfaction rates

The potential of emergent disruptive technologies for humanitarian supply chains: The integration of Blockchain, Artificial Intelligence and 3D Printing

The growing importance of humanitarian operations has created an imperative to overcome the complications currently recorded in the field. Challenges such as delays, congestion, poor communication and lack of accountability may represent opportunities to test the reported advantages of emergent disruptive technologies. Meanwhile, the literature on humanitarian supply chains looks at isolated applications of technology and lacks a framework for understanding challenges and solutions, a gap that this article aims to fill. Using a case study based on the flood of Tabasco of 2007 in Mexico, this research identifies solutions based on the use of emergent disruptive technologies. Furthermore, this article argues that the integration of different technologies is essential to deliver real benefits to the humanitarian supply chain. As a result, it proposes a framework to improve the flow of information, products and financial resources in humanitarian supply chains integrating three emergent disruptive technologies; Artificial Intelligence, Blockchain and 3D Printing. The analysis presented shows the potential of the framework to reduce congestion in the supply chain, enhance simultaneous collaboration of different stakeholders, decrease lead times, increase transparency, traceability and accountability of material and financial resources, and allow victims to get involved in the fulfilment of their own needs

A shortage risk mitigation model for multi-agency coordination in logistics planning

We introduce a two-stage stochastic program to handle typical disaster preparedness activities under uncertainty from a multi-agency perspective. The model explicitly takes into account the number of people without healthcare attention, relief aid, and shelter support. We build a function that represents the total number of people at risk of not receiving proper humanitarian assistance using a bi-objective approach in which expected logistics costs are also minimized. The benefit of our approach is assessed through real flood cases in Mexico in which GIS analysis was used to enhance data gathering and to provide risk maps that could be potentially used by policy-makers in practical settings. The overall results suggest that sheltering decisions have to be closely coordinated with the management of material and human resources to avoid an increased number of people deprived of attention and relief aid. The Pareto Frontier also reveals that some solutions exhibit a quite interesting trade-off, e.g., it is possible to improve the overall relief assistance by almost 17% at the expense of less than 14% in the logistics costs