Extreme Events Decision Making in Transport Networks: A Holistic Approach Using Emergency Scenarios and Decision Making Theory

This paper proposes a novel method to analyse decision-making during extreme events. The method is based on Decision-making Theory and aims at understanding how emergency managers make decisions during disasters. A data collection framework and an analysis method were conceptualized to capture participant’s behaviour, perception and understanding throughout a game-board simulation exercise, which emulates an earthquake disaster scenario affecting transport systems. The method evaluates the participant’s actions in order to identify decision-making patterns, strengths and weaknesses. A set of case studies has shown two typical patterns, namely: a) Support immediate rescue; b) Support lifelines recovery. Good decision-making practices regard to objective-oriented decision making, understanding of conflicting priorities and appropriate resource management. Weaknesses are associated with comprehending relationships between community/environment and projecting future scenarios. Overall, the case study’s results demonstrate the efficiency and robustness of the proposed method to analyse decision making during disasters

Acute stress response for self-optimizing mechatronic systems

Self-optimizing mechatronic systems react autonomously and flexibly to changing conditions. They are capable of learning and optimize their behavior throughout their life cycle. The paradigm of self-optimization is originally inspired by the behavior of biological systems. The key to the successful development of self-optimizing systems is a conceptual design process that precisely describes the desired system behavior. In the area of mechanical engineering, active principles based on physical effects such as friction or lever are widely used to concretize the construction structure and the behavior. The same approach can be found in the domain of software-engineering with software patterns such as the broker-pattern or the strategy pattern. However there is no appropriate design schema for the development of intelligent mechatronic systems covering the needs to fulfill the paradigm of self-optimization. This article proposes such a schema called Active Patterns for Self-Optimization. It is shown how a catalogue of active patterns can be derived from a set of four basic active patterns. This design approach is validated for a networked mechatronic system in a multiagent setting where the behavior is implemented according to a biologically inspired technique – the neuro-fuzzy learning method.1st IFIP International Conference on Biologically Inspired Cooperative Computing - Mechatronics and Computer ClustersRed de Universidades con Carreras en Informática (RedUNCI

Quantifying restoration costs in the aftermath of an extreme event using system dynamics and dynamic mathematical modeling approaches

Extreme events such as earthquakes, hurricanes, and the like, lead to devastating effects that may render multiple supply chain critical infrastructure elements inoperable. The economic losses caused by extreme events continue well after the emergency response phase has ended and are a key factor in determining the best path for post-disaster restoration. It is essential to develop efficient restoration and disaster management strategies to ameliorate the losses from such events. This dissertation extends the existing knowledge base on disaster management and restoration through the creation of models and tools that identify the relationship between production losses and restoration costs. The first research contribution is a system dynamics inoperability model that determines inputs, outputs, and flows for roadway networks. This model can be used to identify the connectivity of road segments and better understand how inoperability contributes to economic consequences. The second contribution is an algorithm that integrates critical infrastructure data derived from bottom-up cost estimation technique as part of an object-oriented software tool that can be used to determine the impact of system disruptions. The third contribution is a dynamic mathematical model that establishes a framework to estimate post-disaster restoration costs from a whole system perspective. Engineering managers, city planners, and policy makers can use the methodologies developed in this research to develop effective disaster planning schemas and to prioritize post-disaster restoration operations --Abstract, page iv

Multi-objective performance optimization of a probabilistic similarity/dissimilarity-based broadcasting scheme for mobile ad hoc networks in disaster response scenarios

Communications among crewmembers in rescue teams and among victims are crucial to relief the consequences and damages of a disaster situation. A common communication system for establishing real time communications between the elements (victims, crewmem-bers, people living in the vicinity of the disaster scenario, among others) involved in a disaster scenario is required. Ad hoc networks have been envisioned for years as a possible solution. They allow users to establish decentralized communications quickly and using common devices like mobile phones. Broadcasting is the main mechanism used to dissemi-nate information in all-to-all fashion in ad hoc networks. The objective of this paper is to optimize a broadcasting scheme based on similari-ty/dissimilarity coefficient designed for disaster response scenarios through a multi-objective optimization problem in which several per-formance metrics such as reachability, number of retransmissions and delay are optimized simultaneously

EVALUATION OF LOCATION SELECTION CRITERIA FOR COORDINATION MANAGEMENT CENTERS AND LOGISTIC SUPPORT UNITS IN DISASTER AREAS WITH AHP METHOD

In recent years, human beings and our planet have suffered great losses in the frequent disasters. Effective and timely intervention is of utmost importance in all large-scale disasters, whether natural or man-made. In this article, a study has been conducted on a model in which the location selection criteria of the management and support centers, where the coordination works as well as the management and administration are carried out in disaster areas, are evaluated by the Multi-Criteria Decision Making (MCDM) method. For this, an in-depth literature analysis was carried out at the first stage, and then all the findings obtained as a result of the literature research were presented to the professionals related to the subject, and expert opinion was sought. In the light of expert opinion, the location selection criteria for the coordination management center and logistic support units in disaster areas were determined, and a model proposal was made, in which the importance values ​​were weighted by using one of the MCDM methods, The Analytic Hierarchy Process (AHP), which is widely used

OPTIMIZATION MODELS AND METHODOLOGIES TO SUPPORT EMERGENCY PREPAREDNESS AND POST-DISASTER RESPONSE

This dissertation addresses three important optimization problems arising during the phases of pre-disaster emergency preparedness and post-disaster response in time-dependent, stochastic and dynamic environments. The first problem studied is the building evacuation problem with shared information (BEPSI), which seeks a set of evacuation routes and the assignment of evacuees to these routes with the minimum total evacuation time. The BEPSI incorporates the constraints of shared information in providing on-line instructions to evacuees and ensures that evacuees departing from an intermediate or source location at a mutual point in time receive common instructions. A mixed-integer linear program is formulated for the BEPSI and an exact technique based on Benders decomposition is proposed for its solution. Numerical experiments conducted on a mid-sized real-world example demonstrate the effectiveness of the proposed algorithm. The second problem addressed is the network resilience problem (NRP), involving an indicator of network resilience proposed to quantify the ability of a network to recover from randomly arising disruptions resulting from a disaster event. A stochastic, mixed integer program is proposed for quantifying network resilience and identifying the optimal post-event course of action to take. A solution technique based on concepts of Benders decomposition, column generation and Monte Carlo simulation is proposed. Experiments were conducted to illustrate the resilience concept and procedure for its measurement, and to assess the role of network topology in its magnitude. The last problem addressed is the urban search and rescue team deployment problem (USAR-TDP). The USAR-TDP seeks an optimal deployment of USAR teams to disaster sites, including the order of site visits, with the ultimate goal of maximizing the expected number of saved lives over the search and rescue period. A multistage stochastic program is proposed to capture problem uncertainty and dynamics. The solution technique involves the solution of a sequence of interrelated two-stage stochastic programs with recourse. A column generation-based technique is proposed for the solution of each problem instance arising as the start of each decision epoch over a time horizon. Numerical experiments conducted on an example of the 2010 Haiti earthquake are presented to illustrate the effectiveness of the proposed approach

Implementing Sustainable Competitive Advantage to the Public Sector's Management System - By Sense & Respond Methodology in Facilities Services Unit's Preparedness

Tutkimuksen tarkoitus on strategian resurssilähtöinen tunnistaminen kestävän kilpailuedun toteuttamiseksi julkisen sektorin hallintajärjestelmässä. Tutkimuksessa arvioidaan empiirisesti kriittiset tekijät (BCFI, SCFI ja NSCFI) tunnistamismenetelmän sovellettavuutta operatiiviseen johtamiseen. Tämä tapahtuu hyödyntämällä strategista analyysiä ja syventämällä tutkimuksen tuloksia ja johtopäätöksiä haastatteluin. Tutkimusmenetelminä ovat tapaustutkimus ja kaksivaiheinen kyselytutkimus, jossa oli yhdistetty analyyttiseen hierarkiaprosessiin pohjautuva lomake ja kaksi Sense & Respond menetelmään pohjautuvaa lomaketta. Kyselytutkimuksessa oli mukana kolme kuudesta Seinäjoen kaupungin hierarkiatasosta. Julkisen sektorin esimies löytää kriittiset tekijät suorituskyvylle parhaiten NSCFI-mallilla. Analyysin perusteella ennen ja jälkeen kriisiä, ennakoivan yksikön vahvimmin vaikuttava strateginen tyyppi on Prospector eli edelläkävijä. Operatiivisen johtamisen näkökulmasta lähiesimiehillä kriittisimmät tekijät ovat tiedon ja teknologian mahdollistamat edellytykset. Kokemukset eivät kohdanneet odotuksia. Saavuttaakseen ylläpitopalvelut yksikön tavoitteet kriittisinä tekijöinä työntekijätasolla ovat tuotteiden, toimintojen ja prosessien laadunhallinta. Tutkimus on tärkeä. Löydökset sekä haastattelut vahvistavat kehittämistoimet. Muuntavan johtamisen tulokset antavat vahvan viitteen varautumiseen ja jatkotutkimuksesta liittyen: operatiivinen kestävä kilpailuetu (OSCA).fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format