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When decisions are made under uncertainty (DMUU), the decision maker either disposes of an interval of possible profits for each alternative (the interval DMUU) or disposes of a discrete set of payoffs for each decision and then the amount of the profit related to a given alternative depends on the state of nature (the scenario DMUU). Existing methods, used to generate the ranking of decisions and applied to the second problem mentioned, take, to a different extent, into consideration how particular profits assigned to alternatives are ordered in the payoff matrix and what the position of a given outcome is in comparison with other outcomes for the same state of nature. The author proposes and describes several alternative procedures that enable connecting the structure of the payoff matrix with the selected decision. These methods are adjusted to the purpose and the nature of the decision maker. They refer to the Savage’s approach, to the maximin joy criterion, to the normalization technique and to some elements used in expected utility maximization and prospect theory.

Scenarios are a new way of representing knowledge that has been attracting a lot of attention from practitioners and researchers. In this paper we present the SDML formalism, an XML definition language to support scenario-based requirements engineering. The definition of scenarios through SDML enables to exploit the emerging XML technologies in order to offer powerful ways to create, maintain, distribute and use scenarios. Moreover, we are experimenting the SDML language on a variety of practical case studies.

In this paper we present SMDP (Scenario Model Development Process), an XML-based methodology for the description and manipulation of scenarios that are used to formalize and reuse software requirements. SMDP is an iterative and incremental process that supports scenario evolution during the requirements engineering process. The formalization of scenarios through the underlying XML-based language of SMDP makes them immediately available to further automatic manipulation (e.g., to automatically generate test cases) without the need for intermediate models, as it is usually done in semi-formal approaches. Thanks to the implementation of a software assistant environment for SMDP, the methodology is currently being experimented on a variety of case studies, in particular web applications.

The scenario-based specifications are popularly used to capture user requirements. The state-based specifications are very appropriate to capture system design. Recently, there has been increased research interest in connecting these two kinds of specifications, called synthesis. Synthesis is a way to automatically construct the state-based specifications from the scenario-based specifications. There are two kinds of synthesis methods: global synthesis and local synthesis. Global synthesis means constructing a state-based specification for the whole system from the scenario-based specifications, while local synthesis means constructing a state-based specification for each object in the system. The two different synthesis methods have different uses and need to be systematically compared. The contributions of this paper are twofold. Firstly, we propose an improved method supporting the global and the local synthesis of state machines (a kind of state-based specifications) by using a novel algorithm for state machine execution and an algorithm similar to operator priority analysis method, which can fully automate the process of synthesis. Our synthesis method also satisfies two important properties: completeness and soundness. Secondly, to the best of our knowledge, our work does the first attempt to systematically compare global synthesis with local synthesis, and shows some insightful results of the experimental comparison between the two kinds of synthesis methods, which are valuable for the practitioners to choose an appropriate synthesis method for the analysis and verification of the system.

Through finite difference time domain (FDTD) numerical simulation, we have studied the possible observation settings to improve the cost effectiveness in time-reversal (TR) source relocation in a two-dimensional (2D) urban setting under a number of typical scenarios. All scenario studies were based on the FDTD computation of the acoustic wave field resulted from an impulse source, propagated through an artificial village composed of 15 buildings and a set of sources and receivers, a typical urban setting has been extensively analyzed in previous studies. The FDTD numerical modeling code can be executed on an off-the-shelf graphic processor unit (GPU) that increases the speed of the time-reversal calculations by a factor of 200. With this approach the computational results lead to some significant conclusions. In general, using only one non-line-of-sight (NLOS) single receiver is not enough to do a quality work to re-locate the source via time-reversal. This is particularly true when there are more than one path between the source and this receiver with similar wave energy travel time. However, when the single sensor is located in an acoustic channel, reverberation inside the waveguide may increase the effective aperture of the single receiver enough to give a good location. It is equivalent to say that the waveguide and the single receiver form a "virtual array". It appears that a sensor array with a minimum number of three receivers might be the most cost-effective way to carry out TR source relocation in an urban environment. The most optimal geometry of a sensor array with a minimum number of three receivers could be an equal side-length triangle. Simple analysis showed that by this setup it is possible to catch sound sources from almost all possible azimuths. Effective source relocation essentially depends on the geometry, relativity to the scatters, etc. of the sensing array. Generally, adding another single sensor relatively far away from the main array will not improve the results. It is practically useful and achievable to have a sensor array mounted on the outside of a single building, and in these cases successful source relocations were obtained. As stated by the fundamental TR theory, increasing the number of scatters, here, increasing the number of buildings will definitely be helpful to increase the effectiveness of TR source relocation.

Manufacturing based corporations often find themselves confronted with complexities of increased pressures to innovate in order to ensure their comparative market positions. In order to react to various exogenous changes corporations need to develop strategies that match their manufacturing resources as well as products with the markets requirements. Product scenarios represent a holistic approach for managing innovation processes and technologies efficiently. The analysis through evolutionary algorithms for compatibility between and amongst the product structure segments provides the necessary information about their suitability. The resulting scenarios, roadmaps and regular monitoring processes are prerequisite for the managerial decision making process and the implementation of product and technology strategies.

In the face of increasing uncertainty in market, technology and political/social trends, scenarios have come to be used to explore how an organisation could plan for a range of possible futures.

This paper outlines four scenarios for the future of UK rail transport up to 2010, developed in the run-up to the privatisation of British Rail in the late 1990s. The scenarios, cost-driven, quality-driven, technology-driven and environment-driven, were produced to identify areas of strategic R&D needed to improve rail's competitiveness in the transport market. Each scenario is illustrated by a typical passenger "journey" and leads to a different set of R&D needs and priorities.

The paper concludes with an assessment of the scenarios five years since they were written, in the light of actual developments since UK rail privatisation. This indicates that the focus to date has been on the cost and quality-driven approaches although there may be a shift towards technological and environmental priorities in the next decade.

Although various user-centric innovation concepts have proved successful in niche markets and specific industries, there is yet little understanding how these models may become more widely diffused in manufacturing industries. We apply an evolutionary economics perspective to explore possible transition pathways towards user-centric innovation paradigms. In order to understand not only the past but also possible future transition trajectories, we complement the co-evolution analysis with prospective elements such as scenario building and roadmapping. Using this combined approach, we identify possible future working configurations of user-centric innovation models and specify a number of diverse elements relevant on different levels of the transition arena. We argue that these insights can be used to define and set-up dedicated learning spaces for user-centric innovation. It is suggested that similar approaches may be useful for companies and policy actors to guide governance of change towards user-centric innovation models.

In urbanising regions, urban sprawl and infrastructure cause profound alterations of natural habitats. Initial decisions on urban expansion and major infrastructure investments are often made on a strategic level where the long-term development of a region is determined. For these types of decisions a strategic environmental assessment can be prepared. However, the lack of an adequate conceptual and methodological framework can pose a major problem for the prediction of impacts, not least concerning biodiversity. This paper will highlight the need for effective methods for biodiversity analysis at landscape and regional levels, with reference to the long-term urban development of the Stockholm and Mälaren regions. Problems of habitat loss, fragmentation and other impacts related to large-scale urbanisation and infrastructure developments will be addressed. GIS-based methods focusing on predictive ecological modelling will be discussed in a scenario context. The implementation of such methodologies in the strategic environmental assessment process would allow a better integration of biodiversity in planning and decision-making, further promoting a sustainable planning system.

The effects of climate change on marine fisheries can be either mitigated by global action on greenhouse gas emission, or managed by encouraging appropriate adaptation. While fishers will autonomously adjust their activities in response to climate change, fisheries management systems may also need to be changed to facilitate adjustment. Identifying the scope of these management changes require some understanding of the impacts of climate change in the absence of any management changes. In this paper, we estimate the climate-related economic impact on Australian marine fisheries and associated sectors for the year 2030, ceteris paribus, based on expected biophysical changes to the resource and using an Input-Output model to capture impacts on the broader economy. Despite considerable uncertainties surrounding potential changes to the biological productivity of capture fisheries, the results suggest that most Australian fisheries and their related sectors could benefit from climate change. Appropriate adaptations could further enhance the benefits and reduce the losses to the fisheries investigated.

Climate change will impact cities’ infrastructure and urban dwellers, who often show differentiated capacity to cope with climate-related hazards. The Shared Socioeconomic Pathways (SSPs) are part of an emerging research field which uses global socioeconomic and climate scenarios, developed by the climate change research community, to explore how different socioeconomic pathways will influence future society’s ability to cope with climate change. While the SSPs have been extensively used at the global scale, their use at the local and urban scale has remained rare, as they first need to be contextualized and extended for the particular place of interest. In this study, we present and apply a method to develop multi-scale extended SSPs at the city and neighborhood scale. Using Boston, Massachusetts, as a case study, we combined scenario matching, experts’ elicitation, and participatory processes to contextualize and make the global SSPs relevant at the urban scale. We subsequently employed the extended SSPs to explore future neighborhood-level vulnerability to extreme heat under multiple plausible socioeconomic trajectories, highlighting the usefulness of extended SSPs in informing future vulnerability assessments. The large differences in outcomes hint at the enormous potential of risk reduction that social and urban planning policies could trigger in the next decades.

This paper describes the financial planning model TnnoALM we developed at Innovest for the Austrian pension fund of the electronics firm Siemens. The model uses a multi period stochastic linear programming framework with a flexible number of time periods of varying length. Uncertainty is modeled using multiperiod discrete probability scenarios for random return and other model parameters. The correlations across asset classes, of bonds. stocks. cash. and other financial instruments. are state dependent using multiple correlation matrices that correspond to differing market conditions. This feature allows lnnoALM to anticipate and react to severe as well as normal market conditions. Austrian pension law and policy considerations can be modeled as constraints in the optimization. The concave risk-averse preference function is to maximize the expected present value of terminal wealth at the specified horizon net of expected discounted convex (piecewise-linear) penalty costs for wealth and benchmark targets in each decision period. lnnoALM has a user interface that provides visualization of key model outputs, the effect of input changes, growing pension benefits from increased deterministic wealth target violations. stochastic benchmark targets, security reserves. policy changes, etc. The solution process using the IBM OSL stochastic programming code is fast enough to generate virtually online decisions and results and allows for easy interaction of the user with the model to improve pension fund performance. The model has been used since 2000 for Siemens Australia, Siemens worldwide. and to evaluate possible pension fund regulation changes in Austria.

We study a theory of dilaton gravity in a 5D brane scenario, with the dilaton nonminimally coupled to the matter content of the universe localized on the brane. We investigate whether the observed large-scale structure of the universe can exist on the brane in the effective 4D dilaton gravity model with an exact anti de Sitter bulk. The corresponding constraint on the spatial derivative of the matter energy density is derived, and subsequently quantified using the current limits resulting from searches for variation of Newton's constant. By confronting it with the observational data from galaxy surveys, we show that the derived bound does not allow for the existence of the large-scale structure as is observed today. Thus, such a dilaton gravity brane scenario is ruled out.