توسعه ی یک سیستم شبیه سازی عامل- مبنا در عملیات امداد و نجات

مدلسازی عامل- مبنا (ABM)[1] رویکردی نوین جهت توسعه‌ی ابزارهای شبیه‌سازی برای پدیده‌های پیچیده در حوزه‌های مختلف از جمله بلایای طبیعی، مطالعات بیولوژیکی و شرایط امداد و نجات زلزله است. این مقاله یک سیستم شبیه‌سازی برای عملیات امداد و نجات با استفاده از سیستم اطلاعات مکانی (GIS)،سیستمهای چندعاملی  (MAS)[2]ومفهـوم هماهنگ‌سازی برای انتساب پویای وظایف بین عامل‌های جستجوگر و عامل‌های آزادساز را ارائه می‌دهد. هدف اصلی این مقاله استفاده ازسیستم‌های چندعاملیبرایشبیه‌سازی فعالیت‌ها، افزایش کـارایی گروه‌های امداد و نجات و ارائه راهکاری جهت یافتن رابطه‌ی بین تعداد عامل‌های جستجوگر و آزادساز با در نظر گرفتن حداکثر تعداد شهروندان نجات یافته می‌باشد. این سیستم می‌تواند برای مدیریت و تصمیم‌گیری قبل از زلزله استفاده شود. ارزیابی سیستم توسعه داده شده در قسمتی از منطقه 3 شهر تهران صورت پذیرفت. سیستم پیشنهادی شامل سه بخش است: مدلسازی محیط و گروه‌های کاری با استفاده از  GIS، تحلیل عملیات جستجو توسط سیستم چندعاملی و بصری‌سازی نتایج.لذا ابتدا محیط با استفاده از داده‌های مکانی مدلسازی شده و سپس مقدار فضایی که هر عامل باید به جست و جو بپردازد برای هر عامل تخصیص داده می‌شود. در ادامه هر یک از عامل‌های جستجوگر از الگوریتم کلونی مورچگان برایترتیب‌دهیوظایف خود در جهت یافتن راه‌حلی نزدیک به بهینه برای جستجوی فضای مطالعاتی استفاده می‌برند. سپسمجروحینپیداشدهتوسطعاملها جست و جوگر، با استفاده از قرارداد شبکه[3] به عامل‌های آزادساز تخصیص داده می‌شوند. نتیجه‌ی این تحقیق در قالب نموداری که رابطه‌ی تعداد عامل‌های جستجوگر و عامل‌های آزادساز (با توجه به تعداد افراد نجات یافته، در صورت هماهنگی عامل‌ها) را نشان می‌دهد ارائه شده است. نتیجه‌ی حاصل الگویی در یافتن تعداد افراد مورد نیاز برای عملیات امداد و نجات در بخش‌های مختلف شهری و برقراری تعادل بین تعداد نفرات را ارائه می‌دهد. [1]3- Agent Based Modeling [2]4- Multi Agent System [3]5- Contract ne

Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach

© 2017, Springer Science+Business Media, LLC. Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a bi-objective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic ε-constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation

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

Integrated business continuity and disaster recovery planning: Towards organizational resilience

Businesses are increasingly subject to disruptions. It is almost impossible to predict their nature, time and extent. Therefore, organizations need a proactive approach equipped with a decision support framework to protect themselves against the outcomes of disruptive events. In this paper, a novel framework is proposed for Integrated Business Continuity and Disaster Recovery Planning for efficient and effective resuming and recovering of critical operations after being disrupted. The proposed model addresses decision problems at all strategic, tactical and operational levels. At the strategic level, the context of the organization is first explored and the main features of the organizational resiliency are recognized. Then, a new multi-objective mixed integer linear programming model is formulated to allocate internal and external resources to both resuming and recovery plans simultaneously. The model aims to control the loss of resiliency by maximizing recovery point and minimizing recovery time objectives. Finally, at the operational level, hypothetical disruptive events are examined to evaluate the applicability of the plans. We also develop a novel interactive augmented ε-constraint method to find the final preferred compromise solution. The proposed model and solution method are finally validated through a real case study

The applicability of the 3C model for understanding the use of technology in emergency management scenarios

The nature of emergency is intensive, imposing challenges related to the way coagencies collaborate. The 3C model consists of the combination of three elements, namely communication, coordination, and cooperation, connecting in a cycle, illustrating the nature of collaborative work for accomplishing certain tasks. Very few studies considered the use of the 3C model for improving collaboration in domains other than emergency management. This paper presents a scoping review of the literature in the domain of emergency management, focusing on how the 3C model can help us understand the use of technology for improving collaboration. The paper identifies the commonalities between the elements of the 3C model for improving our understanding of collaboration in emergency management scenarios, and indicating the inter-relationships among the elements of the 3C model that are applicable for understanding the topology of technology use in emergency management

Disaster management from a POM perspective : mapping a new domain

We have reviewed disaster management research papers published in major operations management, management science, operations research, supply chain management and transportation/ logistics journals. In reviewing these papers our objective is to assess and present the macro level “architectural blue print” of disaster management research with the hope that it will attract new researchers and motivate established researchers to contribute to this important field. The secondary objective is to bring this disaster research to the attention of disaster administrators so that disasters are managed more efficiently and more effectively. We have mapped the disaster management research on the following five attributes of a disaster: (1) Disaster Management Function (decision making process, prevention and mitigation, evacuation, humanitarian logistics, casualty management, and recovery and restoration), (2) Time of Disaster (before, during and after), (3) Type of Disaster (accidents, earthquakes, floods, hurricanes, landslides, terrorism and wildfires etc.), (4) Data Type (Field and Archival data, Real data and Hypothetical data), and (5) Data Analysis Technique (bidding models, decision analysis, expert systems, fuzzy system analysis, game theory, heuristics, mathematical programming, network flow models, queuing theory, simulation and statistical analysis). We have done cross tabulations of data among these five parameters to gain greater insights in disaster research. Recommendations for future research are provided

Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation

Reports of successful implementation of humanitarian optimization models in the field are scarce. Incorporating real conditions and the perspective of decision-makers in the analysis is crucial to enhance the practical value and managerial implications. Although it is known that implementation can be hindered by the lack of practitioner input in the structure of the model, its priorities, and the practicality of solution times, the way these aspects have been introduced in humanitarian optimization models has not been investigated. This study looks at the way research has involved practitioners in different aspects of the design of optimization models to promote implementation. It investigates the aspects affecting the implementation of the models and opportunities to guide future optimization contributions. The article introduces a systematic literature review of 105 articles to answer the research questions. The results are contrasted with a multi-criteria decision analysis using responses from Mexican practitioners. The study found that only 10% of the articles involved practitioners for modelling decisions, which was confirmed by a major gap between the objectives used in the literature and the priorities of Mexican practitioners. In terms of swift decision-making, fewer than 22% of the articles surveyed introduced new solution methods to deliver results in a sensible time. The study also identified very limited inclusion of environmental concerns in the objective functions even though these are a priority in the global agenda. These findings are discussed to propose research directions and suggest best practices for future contributions to promote the implementation of humanitarian logistics models

Location-allocation models for relief distribution and victim evacuation after a sudden-onset natural disaster

Quick response to natural disasters is vital to reduce loss of and negative impact to human life. The response is more crucial in the presence of sudden-onset, difficult-to-predict natural disasters, especially in the early period of those events. On-site actions are part of such response, some of which are determination of temporary shelters and/ or temporary medical facility locations, the evacuation process of victims and relief distribution to victims. These activities of last-mile disaster logistics are important as they are directly associated with sufferers, the main focus of any alleviation of losses caused by any disaster. This research deals with the last-mile site positioning of relief supplies and medical facilities in response to a sudden-onset, difficult-to-predict disaster event, both dynamically and in a more coordinative way during a particular planning time horizon. Four mathematical models which reflect the situation in Padang Pariaman District after the West Sumatera earthquake were built and tested. The models are all concerned with making decisions in a rolling time horizon manner, but differ in coordinating the operations and in utilization of information about future resource availability. Model I is a basic model representing the current practice with relief distribution and victim evacuation performed separately and decisions made only considering the resources available at the time. Model II considers coordination between the two operations and conducts them with the same means of transport. Model III takes into account future information keeping the two operations separate. Model IV combines the features of Models II and III. The four models are approached both directly and by using various heuristics. The research shows that conducting relief distribution and victim evacuation activities by using shared vehicles and/or by taking into account future information on resource availability improves the current practice . This is clearly demonstrated by the experimental results on small problems. For large problems, experiments show that it is not practical to directly solve the models, especially the last three, and that the solution quality is poor when the solution process is limited to a reasonable time. Experiments also show that the heuristics help improve the solution quality and that the performances of the heuristics are different for different models. When each model is solved using its own best heuristic, the conclusions from results of large problems get very close to those from small problems. Finally, deviation of future information on resource availability is considered in the study, but is shown not to affect the performance of model III and model IV in carrying out relief distribution and victim evacuation. This indicates that it is always worthwhile to take into account the future information, even if the information is not perfect, as long as it is reasonably reliable

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