960 resultados para Multiple Criteria


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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.

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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e. the autonomous vehicles’ ability to make appropriate driving decisions in city road traffic situations. After decomposing the problem into two consecutive decision making stages, and giving a short overview about previous work, the paper explains how Multiple Criteria Decision Making (MCDM) can be used in the process of selecting the most appropriate driving maneuver.

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The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.

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A range of funding schemes and policy instruments exist to effect enhancement of the landscapes and habitats of the UK. While a number of assessments of these mechanisms have been conducted, little research has been undertaken to compare both quantitatively and qualitatively their relative effectiveness across a range of criteria. It is argued that few tools are available for such a multi-faceted evaluation of effectiveness. A form of Multiple Criteria Decision Analysis (MCDA) is justified and utilized as a framework in which to evaluate the effectiveness of nine mechanisms in relation to the protection of existing areas of chalk grassland and the creation of new areas in the South Downs of England. These include established schemes, such as the Countryside Stewardship and Environmentally Sensitive Area Schemes, along with other less common mechanisms, for example, land purchase and tender schemes. The steps involved in applying an MCDA to evaluate such mechanisms are identified and the process is described. Quantitative results from the comparison of the effectiveness of different mechanisms are presented, although the broader aim of the paper is that of demonstrating the performance of MCDA as a tool for measuring the effectiveness of mechanisms aimed at landscape and habitat enhancement.

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This paper describes the research supported by a recent AIQS research grant to develop a computer-based tool for sustainability modeling using multiple criteria. The model enables a sustainability index with an accept/reject threshold of one that has the potential to completely replace traditional net present value methods. Minimum performance benchmarks are prescribed and must be observed - often by trading off performance across the full criteria set. Sustainability is shown to be capable of objective (numeric) analysis for new projects, existing facilities, or indeed any product or asset. A combination of investor-centred and community-centred motivations can also be explored in the model. Known as SINDEX, the tool has industry-wide application, both locally and abroad, and represents a paradigm shift in project evaluation techniques. Furthermore, its multi-discipline considerations underscore the importance of a team approach to sustainability modeling and the need for people to work more closely together when dealing with complex problems

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Implementation of integrated catchment management (ICM) is hampered by the lack of a conceptual framework for explaining how landowners select farming systems for their properties. Benefit–cost analysis (a procedure that estimates the costs and benefits of alternative actions or policies) has limitations in this regard, which might be overcome by using multiple-criteria decision analysis (MCDA). MCDA evaluates and ranks alternatives based on a landowner's preferences (weights) for multiple-criteria and the values of those criteria. A MCDA approach to ICM is superior to benefit–cost analysis which focuses only on the monetary benefits and costs, because it: 1) recognizes that human activities within a catchment are motivated by multiple and often competing criteria and/or constraints; 2) does not require monetary valuation of criteria; 3) allows trade-offs between criteria to be measured and evaluated; 4) explicitly considers how the spatial configuration of farming systems in a catchment influences the values of criteria; 5) is comprehensive, knowledge-based, and stakeholder oriented which greatly increases the likelihood of resolving catchment problems; and 6) allows consideration of the fairness and sustainability of land and water resource management decisions. A MCDA based on an additive, multiple-criteria utility function containing five economic and environmental criteria was used to score and rank five farming systems. The rankings were based on the average criteria weights for a sample of 20 farmers in a US catchment. The most profitable farming system was the lowest-ranked farming system. Three possible reasons for this result are evaluated. First, the MCDA method might cause respondents to express socially acceptable attitudes towards environmental criteria even when they are not important from a personal viewpoint. Second, the MCDA method could inflate the ranks of less profitable farming systems for the simple reason that it allows the respondent to assign non-zero weights to non-economic criteria. Third, the MCDA might provide a better framework for evaluating a landowner's selection of farming systems than the profit maximization model.

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Decision support tools will be useful in guiding regions to sustainability. These need to be simple but effective at identifying, for regional managers, areas most in need of initiatives to progress sustainability. Multiple criteria analysis (MCA) is often used as a decision support tool for a wide range of applications. This method allows many criteria to be considered at one time. It does this by giving a ranking of possible options based on how closely each option meets the criteria. Thus, it is suited to the assessment of regional sustainability as it can consider a number of indicators simultaneously and demonstrates how sustainability can vary at small scales across the region. Coupling MCA with GIS to produce maps, allows this analysis to become visual giving the manager a picture of sustainability across the region. To do this each indicator is standardised to a common scale so that it can be compared to other indicators. A weighting is then applied to each indicator to calculate weighted summation for each area in the region. This paper argues that this is the critical step in developing a useful decision support tool. A study being conducted in south west Victoria demonstrates that the weights chosen can have a dramatic impact on the results of the sustainability assessment. It is therefore imperative that careful consideration be given to determining indicator weights in a way that is objective and fully considers the impact of that indicator on regional sustainability.

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This paper describes development of a computer-based tool for sustainability modelling using multiple criteria, and preliminary conclusions from doctoral research being undertaken into the relationship between key sustainability indicators. The model used in both cases produces a sustainability index with an accept/reject threshold of one that has the potential to completely replace traditional net present value methods. Minimum performance benchmarks are prescribed and must be observed - often by trading off performance across the full criteria set. Sustainability is shown to be capable of objective (numeric)· analysis for new projects, existing facilities, or indeed any product or asset. A combination of investor-centred and community-centred motivations can also be explored in the model. Known as SINDEX, the tool has industry-wide application, both locally and abroad, and represents a paradigm shift in project evaluation techniques. Furthermore, its multi-discipline considerations underscore the importance of a team approach to sustainability modelling and the need for people to work more closely together when dealing with complex problems. The results of twenty case studies of actual high schools constructed and operated in New South Wales (Australia) are also presented and the relationships between the key sustainability indicators are explored and interpreted.

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GIS (Geographical Information Systems) based decision support tools will be useful in helping guide regions to sustainability. These tools need to be simple but effective at identifying, for regional managers, areas most in need of initiatives to progress sustainability. Multiple criteria analysis (MCA) has been used as a decision support tool for a wide number of applications, as it provides a systematic framework for evaluating various options. It has the potential to be used as a tool for sustainability assessment, because it can bring together the sustainability criteria from all pillars, social, economic and environmental, to give an integrated assessment of sustainability. Furthermore, the use of GIS and MCA together is an emerging addition to conducting sustainability assessments. This paper further develops a sustainability assessment framework developed for the Glenelg Hopkins Catchment Management Authority region of Victoria, Australia by providing a GIS-based decision support system for regional agencies. This tool uses multiple criteria analysis in a GIS framework to assess the sustainability of sub-catchments in the Glenelg Hopkins Catchment. The multiple criteria analysis based on economic, social and environmental indicators developed in previous stages of this project was used as the basis to build a model in ArcGIS1. The GIS-based multiple criteria analysis, called An Index of Regional Sustainability Spatial Decision Support System (AIRS SDSS),
produced maps showing sub-catchment sustainability, and environmental, social and economic condition. As a result, this tool is able to highlight those sub-catchments most in need of assistance with achieving sustainability. It will also be a valuable tool for evaluation and monitoring of strategies for sustainability. This paper shows the usefulness of GIS-based multiple criteria analysis to enhance the monitoring and evaluation of sustainability at the regional to sub-catchment scale.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Resource allocation is one of the major decision problems arising in higher education. Resources must be allocated optimally in such a way that the performance of universities can be improved. This paper applies an integrated multiple criteria decision making approach to the resource allocation problem. In the approach, the Analytic Hierarchy Process (AHP) is first used to determine the priority or relative importance of proposed projects with respect to the goals of the universities. Then, the Goal Programming (GP) model incorporating the constraints of AHP priority, system, and resource is formulated for selecting the best set of projects without exceeding the limited available resources. The projects include 'hardware' (tangible university's infrastructures), and 'software' (intangible effects that can be beneficial to the university, its members, and its students). In this paper, two commercial packages are used: Expert Choice for determining the AHP priority ranking of the projects, and LINDO for solving the GP model. Copyright © 2007 Inderscience Enterprises Ltd.