Methodological review of multicriteria optimization techniques: aplications in water resources

Multi-criteria decision analysis (MCDA) is an umbrella approach that has been applied to a wide range of natural resource management situations. This report has two purposes. First, it aims to provide an overview of advancedmulticriteriaapproaches, methods and tools. The review seeks to layout the nature of the models, their inherent strengths and limitations. Analysis of their applicability in supporting real-life decision-making processes is provided with relation to requirements imposed by organizationally decentralized and economically specific spatial and temporal frameworks. Models are categorized based on different classification schemes and are reviewed by describing their general characteristics, approaches, and fundamental properties. A necessity of careful structuring of decision problems is discussed regarding planning, staging and control aspects within broader agricultural context, and in water management in particular. A special emphasis is given to the importance of manipulating decision elements by means ofhierarchingand clustering. The review goes beyond traditionalMCDAtechniques; it describes new modelling approaches. The second purpose is to describe newMCDAparadigms aimed at addressing the inherent complexity of managing water ecosystems, particularly with respect to multiple criteria integrated with biophysical models,multistakeholders, and lack of information. Comments about, and critical analysis of, the limitations of traditional models are made to point out the need for, and propose a call to, a new way of thinking aboutMCDAas they are applied to water and natural resources management planning. These new perspectives do not undermine the value of traditional methods; rather they point to a shift in emphasis from methods for problem solving to methods for problem structuring. Literature review show successfully integrations of watershed management optimization models to efficiently screen a broad range of technical, economic, and policy management options within a watershed system framework and select the optimal combination of management strategies and associated water allocations for designing a sustainable watershed management plan at least cost. Papers show applications in watershed management model that integrates both natural and human elements of a watershed system including the management of ground and surface water sources, water treatment and distribution systems, human demands,wastewatertreatment and collection systems, water reuse facilities,nonpotablewater distribution infrastructure, aquifer storage and recharge facilities, storm water, and land use

Balancing stakeholder goals in structural fire design of steel-framed buildings.

When designing a steel-framed building, there are many design options available in terms of meeting the structural fire resistance objectives. Different stakeholders have different opinions about which approach is the most appropriate. A tool or procedure is needed that allows the integration of these diverse stakeholder desires to achieve the most appropriate option. Hence, this research aims to develop this tool. Firstly, extraction and understanding of stakeholder views, along with the capacity to rank them, are needed. However, the challenge is that there are many stakeholder views, so there is also the need to manage these views without ignoring any of them. Towards that some tools are identified in this work to manage different and sometimes divergent stakeholder views to rank them for appropriate decision making. Secondly, to achieve consensus on multiple stakeholder views, the Weighted/Geometric Mean Method (W/GMM) is investigated. Decision analysis techniques including Analytic Hierarchy/Network Processes (AHP/ANP) and Technique of Order of Preference and Similarity to Ideal Solution (TOPSIS) are also studied to understand the influences of stakeholder views on competing design options and to rank the options in the decision-making process. Thirdly, to critically assess the ranking of the design options, a parametric study is needed to predict the suitability and cost-benefit of the various available options. This is carried out by probabilistic analysis of typical structural steel members considering varying parameters and limit state criteria. A probabilistic cost evaluation is also included. Hence, a hybrid design decision analysis tool is developed for the integration of the assessment outcomes to enable the identification of the most cost-effective design option. The final part of this work takes a case study of a realistic building and demonstrates how the process can be applied to structural fire design. This is carried out by integrating and synthesising views from chartered stakeholders and outcomes of the parametric study on representative steel members of the building using the developed hybrid decision analysis tool. The case study follows a risk-based structural fire design decision-making procedure

Implication of national policy on electricity distribution system planning in Kenya

Includes bibliographical references (leaves 131-136).This research project proposes a multi-criteria decision making (MCDM) method of electricity distribution system planning based on the Simple Multi-Attribute Rating Technique (SMART) embedded in a 'bottom-up' planning process to investigate the implication of National Policy (Kenya Vision 2030) on distribution system planning in Kenya. This approach differs from the traditional optimization approaches used in Kenya which typically assesses alternative planning solutions by finding solutions with minimum total cost. Instead a separate capital cost is calculated for each solution, this ensures that the technical benefit of each solution is not obscured by the associated solution capital cost. The approach also allows for effective planning by starting the planning process from the distribution system upward

Assessing the validity of decision support systems : a case study from the sustainable management of the West Bank Aquifer

Decision support systems (DSS) have been widely advocated as key tools for the integrated management of water resources, which emerged as a critical need for addressing the various technical, economic, social, environmental and politicoinstitutional challenges facing the management of water resources. This thesis aims at developing a framework for assessing the validity of DSS in application to water resources management, more particularly reviewing Multi-Criteria Analysis (MCA) and Cost-Benefit Analysis (CBA) as a basis for decision-making. This is critical at times of increasing demand for tools such as DSS, and therefore the increasing importance of overcoming a major DSS limitation, which is validity. The proposed framework consists of two complementary approaches: (1) assessing intra-model validity (MCA), an approach which consists of studying the level of confidence in the comprehensiveness of management options (MO) and basic indicators (BI), analysing uncertainty in the performance values and weights assigned to BI, undertaking a sensitivity analysis of MO ranking to BI performance values and weights, and, based on results, generating as well as evaluating strategy alternatives; (2) assessing DSS inter-model validity, an approach which consists of comparing models (MCA and CBA). The application of the framework to the Sustainable Management of the West Bank Aquifer (SUSMAQ) generates results very much consistent with literature findings: importance of sensitivity analysis as a practical alternative to uncertainty analysis, sensitivity of MO ranking to BI performance values more than to BI weights, importance of accounting for indirect benefits and for the choice of discount rate in CBA, complementarity if not equivalence of MCA and CBA, etc. Although the aim of the thesis is methodological, the application uses validity assessment results to test various strategies for the management of water resources in the West Bank, as an illustrative example only.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Multicriteria methodologies for the appraisal of smart grid projects when flexibility competes with grid expansion

The severe consequences expected due to the increased frequency and intensity of extreme weather events call for improving the environmental sustainability of our society. The electricity sector is pivotal in the path toward a climate-neutral society. Nowadays, the massive use of renewable energy sources requires that electricity demand follows energy production. Demand has to be flexible, as well as the renewable generation and the grid infrastructures. The power system has to assume a decentralised structure and integrate the transportation and cooling and heating sectors. All customers connected to the electrical grid have to contribute to the power system management and participate in the related markets. The power system has to become smart; all technical and market processes have to be digitalised to enable new functionalities and services. The power system transformation requires rethinking planning and operation practices to accommodate the changes and take advantage of the related opportunities. The novel features and services available in the active and flexible power system will influence the customers' daily habits; therefore, the impacts generated by planning initiatives will cross the power system borders by impacting society as a whole. Since the power system will be operated closer to its technical limits, it is crucial to enhance the management of uncertainties by the increased accuracy of load and generation forecast. This thesis addresses the ongoing power system transformation by focusing on the distribution system, which will face unprecedented changes. This thesis concerns novel approaches for appraising the project initiatives based on the use of the users' flexibility connected to the grid. Traditional appraisal tools are no longer effective; therefore, decision-makers have to be supported with tools capable of capturing the complexity of the future power system in which flexibility measures compete with grid expansion. In this thesis, an assessment framework for smart grid initiatives which combines the cost-benefit analysis and the multi-criteria analysis proposed. Based on international guidelines, this framework allows for a systematic and simultaneous assessment of tangible and the intangible impacts considering conflicting criteria. To complete the assessment framework, a novel methodology which combines Regret Theory and multi-criteria analysis is proposed. The proposed methodology represents one of the main contributions of this dissertation. It supports the decision-maker to identify the most valuable option by decomposing the complex decision-making problem of smart grid planning and rejecting personal biases by avoiding the need for defining the evaluation criteria relevance. However, the stakeholders’ perspective can be included in terms of constraints for the minimax optimisation problem. In conclusion, the contribution of the thesis is to provide decision-making support tools for strategical power system planning. The research activities described in this document have been aimed at supporting system operators and regulatory bodies by providing tools for smart grid project appraisal and improving the accuracy of power system studies considering the novel context features

A bi-objective optimization model to eliciting decision maker's preferences for the PROMETHEE II method

Eliciting the preferences of a decision maker is a crucial step when applying multi-criteria decision aid methods on real applications. Yet it remains an open research question, especially in the context of the promethee methods. In this paper, we propose a bi-objective optimization model to tackle the preference elicitation problem. Its main advantage over the widely spread linear programming methods (traditionally proposed to address this question) is the simultaneous optimization of (1) the number of inconsistencies and (2) the robustness of the parameter values. We experimentally study our method for inferring the promethee II preference parameters using the NSGA-II evolutionary multi-objective optimization algorithm. Results obtained on artificial datasets suggest that our method offers promising new perspectives in that field of research. © 2011 Springer-Verlag.SCOPUS: cp.kinfo:eu-repo/semantics/publishe