GIS-based multicriteria analysis as decision support in flood risk management

In this report we develop a GIS-based multicriteria flood risk assessment and mapping approach. This approach has the ability a) to consider also flood risks which are not measured in monetary terms, b) to show the spatial distribution of these multiple risks and c) to deal with uncertainties in criteria values and to show their influence on the overall assessment. It can furthermore be used to show the spatial distribution of the effects of risk reduction measures. The approach is tested for a pilot study at the River Mulde in Saxony, Germany. Therefore, a GISdataset of economic as well as social and environmental risk criteria is built up. Two multicriteria decision rules, a disjunctive approach and an additive weighting approach are used to come to an overall assessment and mapping of flood risk in the area. Both the risk calculation and mapping of single criteria as well as the multicriteria analysis are supported by a software tool (FloodCalc) which was developed for this task. --

Auxiliary Strategies for Water Management in Industries: Minimization of Water Use and Possibility of Recycling and/or Reuse of Effluent

Water management in industry by minimizing water consumption and effluent generation, reusing and/or recycling as a possibility the economy and conservation of water, energy and economic resources. The characterization of the final effluent allows evaluating how much the treatment is adequate to meet the requirements of the regulations of different countries for recycling and/or reuse and evaluated the possibility of reuse, as well as the choice of effluent treatment methods. In this case, technical, environmental and economic criteria, with a view to complying with industrial reuse regulations, should be evaluated, and a multicriteria analysis (MCA) can be adopted to classify the treatment systems applied in different reuse scenarios, made possible by the combination of multiple processes, with the use of tertiary treatment techniques. It should be noted that the potential for recycling and/or reuse of effluents generated in industry increases when effluents are separated into groups (principle of segregation of effluent streams). As a way of promoting a more sustainable model, the use of reuse systems is promising to reduce consumption, as well as reducing operating costs when treating effluents

Grey Numbers in Multiple Criteria Decision Analysis and Conflict Resolution

Definitions of grey numbers are adapted for incorporation into Multiple Criteria Decision Analysis and the Graph Model for Conflict Resolution in order to capture uncertainty in decision making. The main objective is to design improved methods for dealing with decision problems under uncertainty, characterized by limited input data and uncertain preferences of decision makers. A literature review is carried out in order to understand the problems of representing uncertainty using grey numbers within two key decision making contexts: comparing alternative solutions within an multiple criteria decision analysis framework, and deciding upon meaningful courses of action by decision makers involved in a conflict. Then two methodologies that rely on grey numbers to represent uncertain information are provided, and relevant definitions, procedures, and solution concepts are presented

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

A comparative study on decision-making methodology

Decision making (DM), the process of determining and selecting alternative decisions based on information and the preferences of decision makers (DMs), plays a significant role in our daily personal and professional lives. Many DM methods have been developed to assist DMs in their unique type of decision process. In this thesis, DM methods associated with two types of DM processes are studied: Decision-making under uncertainty (DMUU) and Multi-criteria decision making (MCDM). DMUU is making a decision when there are many unknowns or uncertainties about the kinds of states of nature (a complete description of the external factors) that could occur in the future to alter the outcome of a decision. DMUU has two subcategories: decision-making under strict uncertainty (DMUSU) and decision-making under risk (DMUR). Five classic DMUSU methods are Laplace’s insufficient reason principle, Wald’s Maximin, Savage’s Minimax regret, Hurwicz’s pessimism-optimism index criterion and Starr’s domain criterion. Furthermore, based on a review of the relation between a two-player game in game theory and DMUSU, Nash equilibrium is considered a method for approaching DMUSU as well. The well-known DMUR DM methods are expected monetary value, expected opportunity loss, most probable states of nature and expected utility. MCDM is a sub-discipline of operations research, where DMs evaluate multiple conflicting criteria in order to find a compromise solution subject to all the criteria. Numerous MCDM methods exist nowadays. The Analytic Hierarchy Process (AHP), the ELimination et Choix Traduisant la REalité (ELECTRE), the Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are the most employed of all the various MCDM methods. This PhD work focuses on presenting a comparative study of DM methods theoretically and evaluating the performance of different methods on a single decision problem. This contribution can guide DMs in gathering the relative objective and subjective information, structuring the decision problem and selecting the right DM method to make the decision that suits not only their subjective preferences, but also the objective facts. The case study used here is the selection of a sewer network construction plan. It is a representative and complex practical decision problem that requires the quality, life-cycle maintenance and performance of the selected sewer system to meet long-term planning for future climate changes and urban development. La prise de décision (DM), un processus de détermination et de sélection de décisions alternatives en fonction des informations et des préférences des décideurs (DM), apparaît largement dans notre vie personnelle et professionnelle quotidienne. Un grand nombre de méthodes DM ont été développées pour aider les DM dans leur type unique de processus de décision. Dans cette thèse, les méthodes DM associées à deux types de processus DM sont étudiées : la prise de décision sous incertitude (DMUU) et la prise de décision multicritère (MCDM). La DMUU doit prendre la décision lorsqu'il existe de nombreuses inconnues ou incertitudes sur le type d'états de la nature (une description complète des facteurs externes) qui pourraient se produire à l'avenir pour modifier le résultat d'une décision. La DMUU comprend deux sous-catégories : la prise de décision sous incertitude stricte (DMUSU) et la prise de décision sous risque (DMUR). Cinq méthodes classiques de DM pour DMUSU sont le principe de raison insuffisante de Laplace, le Waldimin Maximin, le regret Savage Minimax, le critère d'index pessimisme-optimisme de Hurwitz et le critère de domaine de Starr. En outre, l'examen de la relation entre un jeu à deux joueurs dans la théorie des jeux et l'équilibre DMUSU et Nash Equilibrium est également considéré comme l'une des méthodes pour résoudre le DMUSU. Les méthodes DM bien connues de DMUR sont la valeur monétaire attendue, la perte d'opportunité attendue, les états de nature les plus probables et l'utilité attendue. Le MCDM est une sous-discipline de la recherche opérationnelle, où les DM évaluent plusieurs critères conflictuels afin de trouver la solution compromise soumise à tous les critères. Un certain nombre de méthodes DM pour MCDM sont présentes de nos jours. Le processus de hiérarchie analytique (AHP), l'élimination et le choix traduisant la réalité (ELECTRE), les méthodes d'organisation du classement des préférences pour les évaluations d'enrichissement (PROMETHEE) et la technique de préférence par ordre de similitude et de solution idéale (TOPSIS) sont les plus choisies et utilisées des méthodes parmi toutes les différentes méthodes MCDM. Ce travail de thèse se concentre sur la présentation théorique d'une étude comparative des méthodes DM et l'évaluation des performances de différentes méthodes avec un problème de décision particulier. Cette contribution peut guider les DM à rassembler les informations relatives objectives et subjectives, à structurer le problème de décision et à sélectionner la bonne méthode de DM pour prendre la décision qui convient non seulement à leurs préférences subjectives, mais aussi aux faits objectifs. L'étude de cas utilisée ici est la sélection du plan de construction du réseau d'égouts. Il s'agit d'un problème de décision pratique représentatif et complexe qui nécessite la qualité, l'entretien du cycle de vie et les performances du réseau d'égouts sélectionné pour répondre à la planification à long terme des futurs changements climatiques et du développement urbain

Assessing optimal water quality monitoring network in road construction using integrated information-theoretic techniques

Author´s accepted manuscript.The environmental impacts of road construction on the aquatic environment necessitate the monitoring of receiving water quality. The main contribution of the paper is developing a feasible methodology for spatial optimization of the water quality monitoring network (WQMN) in surface water during road construction using the field data. First, using the Canadian Council of Ministers of the Environment (CCME) method, the water quality index (WQI) was computed in each potential monitoring station during construction. Then, the integrated form of the information-theoretic techniques consists of the transinformation entropy (TE), and the value of information (VOI) were calculated for the potential stations. To achieve the optimal WQMNs, the Non-dominated Sorting Genetic Algorithm II and III (NSGA-II, and III) based multi-objective optimization models were developed considering three objective functions, including i) minimizing the number of stations, ii) maximizing the VOI in the selected network, and iii) minimizing redundant information for the selected nodes. Finally, three multi-criteria decision-making models, including Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE), and Analytical Hierarchy Process (AHP) were utilized for choosing the best alternative among Pareto optimal solutions considering various weighing scenarios assigned to criteria. The applicability of the presented methodology was assessed in a 22 km long road construction site in southern Norway. The results deliver significant knowledge for decision-makers on establishing a robust WQMN in surface water during road construction projects.publishedVersio

A Review and Classification of Approaches for Dealing with Uncertainty in Multi-Criteria Decision Analysis for Healthcare Decisions

Multi-criteria decision analysis (MCDA) is increasingly used to support decisions in healthcare involving multiple and conflicting criteria. Although uncertainty is usually carefully addressed in health economic evaluations, whether and how the different sources of uncertainty are dealt with and with what methods in MCDA is less known. The objective of this study is to review how uncertainty can be explicitly taken into account in MCDA and to discuss which approach may be appropriate for healthcare decision makers. A literature review was conducted in the Scopus and PubMed databases. Two reviewers independently categorized studies according to research areas, the type of MCDA used, and the approach used to quantify uncertainty. Selected full text articles were read for methodological details. The search strategy identified 569 studies. The five approaches most identified were fuzzy set theory (45 % of studies), probabilistic sensitivity analysis (15 %), deterministic sensitivity analysis (31 %), Bayesian framework (6 %), and grey theory (3 %). A large number of papers considered the analytic hierarchy process in combination with fuzzy set theory (31 %). Only 3 % of studies were published in healthcare-related journals. In conclusion, our review identified five different approaches to take uncertainty into account in MCDA. The deterministic approach is most likely sufficient for most healthcare policy decisions because of its low complexity and straightforward implementation. However, more complex approaches may be needed when multiple sources of uncertainty must be considered simultaneousl

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems