Technical Conception and Implementation of an IT-System supporting the flexible Distribution of Documents within a large scale Sales Organization

This thesis aims to discuss and present an IT system to distribute documents within a large scale sales organization. Therefore, different sales applications on the market are analyzed and described. Based on this analysis, requirements for the IT system are defined. The requirements are divided into client-side and server-side requirements. The server application is realized using an existing ECM system to support the content throughout the enterprise content life cycle. Therefore, an evaluation of existing ECM systems is performed with a criteria catalog based on the requirements. Afterwards, the conception and architecture of the IT system is described, followed by further insights into the technical implementation of the mobile application. Finally, the features of the overall IT system are discussed and an outlook on how to extend the IT system is presented

Sustainable cycle-tourism for society: Integrating multi-criteria decision-making and land use approaches for route selection

Cycle tourism is a sustainable active vacation, which is quickly growing in recent years. Although it has several benefits for society and users (e.g., social connections, amusement, and physical and mental health), cycle tourism requires an adequate route network to enjoy destinations with historical and landscape peculiarities. Past literature mainly investigated motivations and preferences for cycle tourists and proposed optimisation methods in planning routes. However, applying assessment methods for prioritising cycle-tourist routes is a seldom-explored topic. This study aims to address this gap by applying an integrated method for evaluating and prioritising cycle routes, searching for a compromise between route characteristics, service provided to users, and natural and building contexts crossed. It jointly includes Multi-Criteria Decision Methods (MCDMs) and a land use approach: AHP determines the weights of criteria and parameters describing cycle routes; GIS elaborates spatial analysis of parameters; ELECTRE I and VIKOR help find a compromise solution amongst different cycle routes. The integrated method involved a panel of experts to collect data, and it is applied to the wide-study area of Franciacorta (Italy). Some comparisons with other MCDMs are made to justify the results. The findings could support multi-institutions prioritising cycle route alternatives in deciding their building

Ranking of hydropower projects based on sustainability criteria in India using multicriteria decision making methods

Assessment of hydropower projects with respect to sustainability criteria is a multidimensional and complex issue. It requires considering technical, environmental, and social parameters instead of purely economic ones in decision making for energy planning. The flexibility to consider several criteria and objectives simultaneously leads to the use of multicriteria decision making (MCDM) methods which are well accepted in the field of energy planning. This paper aims at applying MCDM methods in facilitating the decision makers to select the most sustainable hydropower projects in the Indian region by making real and logical choices based on eight important criteria selected from the literature that are compatible with sustainable development. To comprehensively rank hydropower projects three MCDM methods are applied i.e., the technique for order of preference by similarity to ideal solution (TOPSIS), preference ranking organization method for enrichment evaluations (PROMETHEE II), and elimination and choice translating reality (ELECTRE III). Analytic hierarchy process (AHP) is used to calculate the weights of criteria. All three methods are well adapted for sustainability assessment and ranked Sharavathi (A9), Bhakra (A2), and Upper Indravati (A13) to be the most sustainable hydropower projects in India under the selected criteria. The study will be helpful in sustainable energy planning of hydropower projects with similar geographical conditions

A Decision Tool for Supplier Selection That Takes into Account Power and Performance

Companies select their suppliers to provide required performance while being successful partners. An important aspect of collaboration is the power relationship between the company and its suppliers. Although the significance of power in supplier selection is acknowledged, published work rarely includes assessment of power. An empirical study on selecting suppliers for new product developments in a major European diesel engine manufacturing company, supported by three smaller studies with electronic engineering companies, frames overall questions regarding the importance of incorporating power into supplier selection and how this might be achieved. This research proposes an approach that assesses both performance and power and integrates the assessment results by modelling the relative effects of power and performance. It positions the suppliers into six scenarios (ideal, satisfying, tolerable, unfavourable, risky and tough) which depict to what extent a supplier is ‘suitable’ to work with. A reverse analysis reviews the relationship when several suppliers appear suitable. An assessment method is developed incorporating both subjective and objective data for qualitative and quantitative criteria. It combines two decision making methods, AHP and TOPSIS, with triangular fuzzy numbers. Multiple judgements from several decision makers are synthesised. This method is adapted for performance assessment of single, group and cross-group suppliers. Weights are calculated for the criteria, and combined with calculations of supplier performance against each criterion to provide an overall assessment and supplier profile. Power is quantified against a set of power determinants and power relations (supplier dominance, buyer dominance and balanced) are determined. The effects of supplier perceptions (objective, optimistic and pessimistic) are estimated in the calculation. The proposed approach involves complex calculations and a prototype software tool is developed with graphical interfaces. The tool includes performance criteria and power determinants collected from literature and allows users to define new ones. Application to an agriculture case enables the sustainable performance of suppliers (farmers) to be evaluated and compared

Multi-criteria decision-making in whole process design

PhD ThesisIn recent years, the chemical and pharmaceutical industries have faced increased development times and costs with fewer novel chemicals being discovered. This has resulted in many companies focusing on innovative research and development as they consider this key to business success. In particular, a number of leading industrial organisations have adopted the principles of Whole Process Design (WPD). WPD considers the optimisation of the entire product development process, from raw materials to end product, rather than focusing on each individual unit operation. The complexity involved in the implementation of WPD requires rationalised decision-making, often with limited or uncertain information. This thesis assesses the most widely applied methods in Multi-Criteria Decision Analysis (MCDA) in conjunction with the results of two interviews and two questionnaires that identified the industrial requirements for decision-making during WPD. From the findings of this work, a novel decision-making methodology was proposed, the outcome of which allows a decision-maker to visually interpret their decision results with associated levels of uncertainty. To validate the proposed methodology, a software framework was developed that incorporates two other decision-making approaches, the Analytical Hierarchy Process (AHP) and ELimination Et Choix Traduisant la REalité trois (ELECTRE III). The framework was then applied to a number of industrial case studies to validate the application of the proposed methodology.Engineering and Physical Sciences Research Council (EPSRC) and Chemistry Innovatio

Data Normalization in Decision Making Processes

With the fast-growing of data-rich systems, dealing with complex decision problems is unavoidable. Normalization is a crucial step in most multi criteria decision making (MCDM) models, to produce comparable and dimensionless data from heterogeneous data. Further, MCDM requires data to be numerical and comparable to be aggregated into a single score per alternative, thus providing their ranking. Several normalization techniques are available, but their performance depends on a number of characteristics of the problem at hand i.e., different normalization techniques may provide different rankings for alternatives. Therefore, it is a challenge to select a suitable normalization technique to represent an appropriate mapping from source data to a common scale. There are some attempts in the literature to address the subject of normalization in MCDM, but there is still a lack of assessment frameworks for evaluating normalization techniques. Hence, the main contribution and objective of this study is to develop an assessment framework for analysing the effects of normalization techniques on ranking of alternatives in MCDM methods and recommend the most appropriate technique for specific decision problems. The proposed assessment framework consists of four steps: (i) determining data types; (ii) chose potential candidate normalization techniques; (iii) analysis and evaluation of techniques; and (iv) selection of the best normalization technique. To validate the efficiency and robustness of the proposed framework, six normalization techniques (Max, Max-Min, Sum, Vector, Logarithmic, and Fuzzification) are selected from linear, semi-linear, and non-linear categories, and tested with four well known MCDM methods (TOPSIS, SAW, AHP, and ELECTRE), from scoring, comparative, and ranking methods. Designing the proposed assessment framework led to a conceptual model allowing an automatic decision-making process, besides recommending the most appropriate normalization technique for MCDM problems. Furthermore, the role of normalization techniques for dynamic multi criteria decision making (DMCDM) in collaborative networks is explored, specifically related to problems of selection of suppliers, business partners, resources, etc. To validate and test the utility and applicability of the assessment framework, a number of case studies are discussed and benchmarking and testimonies from experts are used. Also, an evaluation by the research community of the work developed is presented. The validation process demonstrated that the proposed assessment framework increases the accuracy of results in MCDM decision problems.Com o rápido crescimento dos sistemas ricos em dados, lidar com problemas de decisão complexos é inevitável. A normalização é uma etapa crucial na maioria dos modelos de tomada de decisão multicritério (MCDM), para produzir dados comparáveis e adimensionais a partir de dados heterogéneos, porque os dados precisam ser numéricos e comparáveis para serem agregados em uma única pontuação por alternativa. Como tal, várias técnicas de normalização estão disponíveis, mas o seu desempenho depende de uma série de características do problema em questão, ou seja, diferentes técnicas de normalização podem resultar em diferentes classificações para as alternativas. Portanto, é um desafio selecionar uma técnica de normalização adequada para representar o mapeamento dos dados de origem para uma escala comum. Existem algumas tentativas na literatura de abordar o assunto da normalização, mas ainda há uma falta de estrutura de avaliação para avaliar as técnicas de normalização sobre qual técnica é mais apropriada para os métodos MCDM.Assim, a principal contribuição e objetivo deste estudo são desenvolver uma ferramenta de avaliação para analisar os efeitos das técnicas de normalização na seriação de alternativas em métodos MCDM e recomendar a técnica mais adequada para problemas de decisão específicos. A estrutura de avaliação da ferramenta proposta consiste em quatro etapas: (i) determinar os tipos de dados, (ii) selecionar potenciais técnicas de normalização, (iii) análise e avaliação de técnicas em problemas de MCDM, e (iv) recomendação da melhor técnica para o problema de decisão. Para validar a eficácia e robustez da ferramenta proposta, seis técnicas de normalização (Max, Max-Min, Sum, Vector, Logarithmic e Fuzzification) foram selecionadas - das categorias lineares, semilineares e não lineares- e quatro conhecidos métodos de MCDM foram escolhidos (TOPSIS, SAW, AHP e ELECTRE). O desenho da ferramenta de avaliação proposta levou ao modelo conceptual que forneceu um processo automático de tomada de decisão, além de recomendar a técnica de normalização mais adequada para problemas de decisão. Além disso, é explorado o papel das técnicas de normalização para tomada de decisão multicritério dinâmica (DMCDM) em redes colaborativas, especificamente relacionadas com problemas de seleção de fornecedores, parceiros de negócios, recursos, etc. Para validar e testar a utilidade e aplicabilidade da ferramenta de avaliação, uma série de casos de estudo são discutidos e benchmarking e testemunhos de especialistas são usados. Além disso, uma avaliação do trabalho desenvolvido pela comunidade de investigação também é apresentada. Esta validação demonstrou que a ferramenta proposta aumenta a precisão dos resultados em problemas de decisão multicritério

A study of regret and rejoicing and a new MCDM method based on them

Multi-criteria decision-making (MCDM) is one of the most widely used decision methodologies in the sciences, business, and engineering worlds. MCDM methods aim at improving the quality of decisions by making the process more explicit, rational, and efficient. One controversial problem is that some well-known MCDM methods, like the additive AHP methods and the ELECTRE II and III methods, may cause some types of rank reversal problems. Rank reversal means that the ranking between two alternatives might be reversed after some variation occurs to the decision problem, like adding a new alternative, dropping an old alternative or replacing a non-optimal alternative by a worse one etc. Usually such a rank reversal is undesirable for decision-making problems. If a method does allow it to happen, the validity of the method could be questioned. However, some recent studies indicate that rank reversals could also happen because of people’s rational preference reversal which may be caused by their emotional feelings, like regret and rejoicing. Since regret and rejoicing may play a pivotal role in evaluating alternatives in MCDM problems, sometimes the decision maker (DM) may want to anticipate these emotional feelings and consider them in the decision-making process. Most of the regret models in the literature use continuous functions to measure this emotional factor. This dissertation proposes to use an approach based on a linguistic scale and pairwise comparisons to measure a DM’s anticipated regret and rejoicing feelings. The approach is shown to exhibit some key advantages over existing approaches. Next a multiplicative MCDM model is adopted to aggregate the alternatives’ associated regret and rejoicing values with their performance values to get their final priorities and then rank them. A simulated numerical example is used to illustrate the process of the proposed method. Some sensitivity analyses which aim at examining how changes of regret and rejoicing values might affect the ranking results of the decision problems are also developed. Then a fuzzy version of the new method is introduced and illustrated by a numerical example. Finally, some concluding remarks are made. Ranking intransitivity and some other issues about the proposed method are analyzed too