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A natural phenomenon often entails considerable consequences, such as the destruction of infrastructures and the loss of human lives. However, the number of casualties does not only depend on the severity of the natural phenomena but also on the effectiveness of the Urban Search And Rescue (USAR) operations, coordinated by the Operation Center (OC). The number of the incoming information is usually large, while the available USAR teams are limited, resulting in misleading decisions, regarding the prioritizing of the USAR operations, and huge delays. This ineffectiveness could result in a disproportionate number of casualties and decline the civilians' trust to the national and local government, producing political instability to the region or the country. Thus, an automated process, which prioritize the USAR operations is absolutely necessary, in order to ensure that the OC will take the best possible decisions in minimum time. In this study, a methodology is developed, regarding the production of prioritization maps (heatmaps), which identify and prioritize the most critical regions in an area prior to the occurrence of the natural disaster. At the time that the natural disaster occurs, their use from the OC, combined with the incoming information, will contribute to an effective and quick decision-making process, which in turn will minimize the casualties, and ensure the rapid return to normality and stability of the whole area. In order to develop this methodology several scenarios are taken into account, depending on the time and the day of the natural disaster and determining the most likely distribution of the population in the area under consideration. Statistical data (population and building data) and data of vulnerable social groups (eg disabled persons, children) are processed in Geographic Information Systems (GIS) to develop heatmaps. Finally, the previous described methodology has been applied for the municipality of Agia Paraskevi (a suburb of Athens), and the corresponding heatmaps are developed. The produced maps present the most critical areas of the municipality and their use, in a case of a natural disaster, is expected to enhance the effectiveness of USAR teams ensuring political stability. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

The main purpose of this paper is the formulation of a methodological approach for the definition of homogenous spatial clusters, taking into account both geographical and descriptive characteristics. The proposed methodology, is substantiated by SPiRAL (SPatial Integration and Redistricting ALgorithm), a constrained-based spatial clustering algorithm, whose successive steps focus on the analysis of the characteristics of the areas being integrated, the designation of the spatial clusters and the validity of a joining criterion. We applied the methodological approach and used SPiRAL to solve a realistic electoral redistricting problem. Namely, the redefinition of the electoral districts of the Prefecture of Lakonia in Greece. The results demonstrate an improved layout of the study area’s electoral map as far as the problem’s criteria and constraints are concerned (adjacency, population and size), justifying in this respect the perspectives and potential of our approach in the analysis and confrontation of similar problems.

After the intense and unprecedented urbanisation of the last centuries, it is more than evident that a clear understanding of the ongoing trends of urban growth and clustering is needed if we are to aim for a better insight as to their possible future. The main aim of this paper is the definition of a methodological framework for the determination, analysis and cross-evaluation of urban clusters which are formulated within wider study areas, such as administrative regions. To this end, different methods and techniques are utilised, that stem from the fields of Statistics and Quantitative Spatial Analysis and which, during recent years, are all the more commonly applied to the different stages of Geographical Analysis. The definition of urban clusters is mainly based on different types of variables, such as the demographic characteristics of the cities, the number of public and private sector services located in them, as well as the total length of the different types of road network in the study area. Furthermore, a comparative indicator of spatial concentration is formulated that reflects the role and the relative weight of every urban area in the study region as well as its spatial influence. Such a measurement improves the definition and analysis of urban clusters and at the same time, constitutes an alternative assessment of their overall locational perspective. Both the proposed methodological framework and the formulated indicator are applied in the region of Thessaly, Greece.

The prospect for establishing a General Clinic at the Thessaly Region was examined. The new facility aimes to provide full medical care by qualified scientists (permanent personnel, shareholders or associates), by experienced, trained and skilled nursing personnel, fully organised with sophisticated technological equipment, in a hospitable and pleasant environment, with easy and fast access. The main aim of this study is the determination of the optimum location for the construction of the proposed medical centre for providing high level services in the Thessaly region, by implementing quantitative methods of Spatial Analysis of GIS technology. Spatial Analysis focuses on evaluating existing and proposed models of spatial organization, while GIS, provide the necessary informational tools for the elaboration and management of the relevant information and all in all in the support of the relevant decision making process.

Enterprises seek for development and growth so as to increase their sales and profits. In order to come to a decision on how this development is going to be achieved they face an endless line of possible strategies, one of which is location. Location of the business affects its development and viability, concerning the cost, its efficiency and its use. Regarding the location of the centers of providing medical services despite the new technologies (like telemedicine ‐ which facilitates the reaction to a distant event), their location continue to be a distinctive advantage since immediate access and service is the objective target. Significant factors are the nature of the situations a facility has to face as well as the displacement time both in cases of diagnosis and in cases of remedies, which is important and in various cases decisive. Additionally to the best location, the best possible cooperation with specialized doctors and nursery personnel from the wider region is required. In this framework, Spatial Analysis and Geographical Information Systems are recruited to demonstrate how all the above issues can be answered under the complex environment a location‐allocation decision must be taken, by the authorities for the location‐allocation of health infrastructure.

While during the past decades, urban areas experience constant slow population growth, the spatial patterns they form, by means of their limits and borders, are rapidly changing in a complex way. Furthermore, urban areas continue to expand to the expense of "rural” intensifying urban sprawl. The main aim of this paper is the definition of the evolution of urban areas and more specifically, the specification of an urban model, which deals simultaneously with the modification of population and building use patterns. Classical theories define city geographic border, with the Aristotelian division of 0 or 1 and are called fiat geographic boundaries. But the edge of a city and the urbanization "degree" is something not easily distinguishable. Actually, the line that city ends and rural starts is vague. In this respect a synthetic spatio - temporal methodology is described which, through the adaptation of different computational methods aims to assist planners and decision makers to gain an insight in urban - rural transition. Fuzzy Logic and Neural Networks are recruited to provide a precise image of spatial entities, further exploited in a twofold way. First for analysis and interpretation of up - to - date urban evolution and second, for the formulation of a robust spatial simulation model, the theoretical background of which is that the spatial contiguity between members of the same or different groups is one of the key factors in their evolution. The paper finally presents the results of the model application in the prefecture of Attica in Greece, unveiling the role of the Athens Metropolitan Area to its current and future evolution, by illustrating maps of urban growth dynamics.

The efficiency of emergency service systems is measured in terms of their ability to deploy units and personnel in a timely and effective manner upon an event’s occurrence. Aiming to exploit stochastic demand, spatial tracing and location analysis of emergency incidents are examined through the utilisation of Artificial Intelligence in two interacting levels. Firstly, spatio-temporal point pattern of demand is analysed by a new genetic algorithm. The proposed genetic algorithm interrelates sequential events formulating moving events and as a result, every demand point pattern is correlated both to previous and following events. Secondly, the approach provides the ability to predict, by means of neural networks optimised by genetic algorithms, how the pattern of demand will evolve and thus location of supplying centres and/or vehicles can be optimally defined. Neural networks provide the basis for a spatio-temporal clustering of demand, definition of the relevant centres, formulation of possible future states of the system and finally, definition of locational strategies for the improvement of the provided services.

There is no doubt that even a cursory examination of the indisputable efforts for decentralization in Greece, will reveal that the main problem lies within the ever expanding bureaucratic labyrinth of its political decision making processes and the underlying political and administrative system that generates and supports them. In short, this political system seems to strive for inclusiveness and broad acceptance, rather than theoretical consistency or elegance, setting the government incapable to play a truly coordinating role and exhibit the admistrative wisdom that it implies. Seeking in this respect, to accommodate new demands as they emerge by means, insofar as possible, that leave previous arrangements (programs and administrative regulations) undisturbed, which in turn involve the least possible disruption for public enterprises, as well as the least possible inconvenience and annoyance for institutions and individuals alike, who have built their life styles around the expectation of system stability. However, in terms of its administrative system, Greece has the same characteristics and problems with most of the Mediterranean European Countries. Consequently, the potential of future decentralization policies in a regional level, as they are expressed by either the elimination of regional disparities or the formulation of regional restructuring strategies, should be seen with respect to the extended political framework within which they have to be implemented. In our study, this is defined as the Mediterranean frontier. Within this framework, this paper reviews the historical course and critically presents the results of the proclaimed decentralization efforts in Greece. Specifically, certain political and socioeconomic indicators are utilized, in order both to micro evaluate the regional disparities within the country and to generate a parallel macro comparison with the other Mediterranean member states of the European Union.

Since population, which actually represents demand in any organised or rearranged service system, is the final target and recipient of every planning strategy or policy action, the success of locational analysis and the locational planning process, is largely determined upon the decision makers' ability to estimate the study area's future population size and distribution. Such estimations can be demographically achieved through the analysis and extrapolation into the future of carefully measured birth, death and migration rates according to observed trends and tendencies of the relevant socio-economic factors that affect them. As opposed to traditional generalisations and recent practices, which deal with population as a whole, the approach presented in this paper focuses on each individual's attitude towards the issue of intended births, which when aggregated formulate a fertility rate. More specifically, certain socio-economic characteristics, based on questionnaire data, are analysed using discrete choice models in order to estimate the prospective family-size desires. In this respect, a birth-rate choice model is derived through the assessment of the expected number of children to be born in a household during a specific time period and with regard to its socio-economic identity. Moreover, modifications of the above characteristics generate alternative family-size scenarios and thus differing population forecasts, which in turn can lead to unforeseen solution strategies and thus a more sophisticated and pragmatic decision-making process when dealing with facility-location problems both in the public and the private sector.

In this paper we describe a case study of our attempt to provide decision support to a public agency, the Greek Ministry of Education, that is currently reorganizing the geo¬graphical configuration of its system. We treat the problem of determining the optimal number of catch¬ment areas, the school locations and the allocations of school children, as an interactive location-allocation problem. In our approach and during the problem-solving procedure, we deal with a set of predefined future scenarios, emphasizing on the uncertainty principles emerging from the notion of a popula¬tion being subject to elements of change. The scenarios are generated from an initial dataset, through the implementation of certain demographic assumptions, concerning fertility, mortality and migration rates. By linking demographic and locational models, and using the graphic capabilities of mapping software, we provide the basis for an integrated locational planning support system and thus a more pragmatic planning process. Furthermore, we assist the decision making process through the utilization of two solution - perform¬ance criteria. Namely, the expected loss and the minimax loss criterion of the optimal solution of each future scenario configur¬ation which is gener¬ated during the problem solving procedure.

More and more frequently locational planners are faced with the problem of decision making under the condition of uncertainty. In this paper a methodological framework is presented for solving Location - Allocation problems, through the application of the multinomial logit model to data derived from the modification of the characteristics of a given network. The study differs from earlier work in two aspects: First, a utility junction, as a measure of relative attractiveness, is implemented, in order to assign realization probabilities to each alternative scenario. Second, the decisions are made through the utilization of two system - performance criteria. The expected loss and the minimax loss criterion of the optimal solution of each future scenario generated by the decision maker during the problem - solving procedure of th e approach.