Dissertation thesis focuses on principles of multi-criteria decision-making in public contracts. The theoretical section of the thesis introduces principles and methods of multi-criteria decision-making including the determination of their suitability for public contracts. It also cover characteristics and specifics of purchasing via public contracts and findings of previous research conducted in the Czech Republic and foreign countries. Own empirical research comprises two parts. The first part of research is based on data about public contracts from the Czech Republic between 2011 and 2013 announced via the Information System on Public Contracts. The data allow investigating criteria and their weights used by contracting entities in relationship to characteristics of the public contracts; especially the subject-matter and the value of the contract. The second part of the research is based on sample data file of contract announcements for contracts evaluated according to the economic advantageousness of the tender. The data allow investigating methods of multi-criteria decision making and approaches to qualitative criteria. Findings from the theory and the conducted research were source for a normative model for selection of criteria and methods of multi-criteria decision-making. The goal of the model is to enhance the quality of decision-making in the field of public contracts. The most important contribution of the model is the connection of the three key parts of multi-criteria decision-making; criteria, its weights and methods of multi-criteria decision-making.

This Master´s Thesis focuses on the issue of renewal of fleet in Deblice-lesy, s.r.o. company. The aim of this thesis is selection of suitable semitrailer combination for transportation of long timbers and also selection of truck for transportation of ACTS containers for transportation of firewood, which will correspond to the selected criteria. Selection will be realized by using TOPSIS method. Theoretical part focuses on issues of business in road transport, trucks and combinations in road transport and limits of their dimensions and weights. It also describes some methods of multi-criteria decision making. Practical part focuses directly on selection of suitable semitrailer combination for transportation of long timbers and also selection of truck for transportation of ACTS containers according to the defined criteria. One of the aims is also mapping of the market and choices which exist when selecting combination for transportation of long timbers.

L'aide à la décision multicritères regroupe des méthodes permettant de choisir la meilleure solution en fonction des différents critères et compte tenu des préférences des experts. Toutefois, ces préférences sont parfois exprimées de manière imparfaite. La théorie des fonctions de croyance modélise de manière souple les connaissances et fournit des outils mathématiques pour gérer les différents types d'imperfection. Ainsi dans cette thèse, nous nous intéressons à la prise de décision multicritères dans un cadre incertain en étendant la méthode d’Analyse Hiérarchique des Procédés (AHP) à la théorie des fonctions de croyance. Après avoir présenté les fondements théoriques de la méthode AHP, nous avons proposé une approche qui permet de réduire le nombre de comparaisons par paires en jugeant des sous-ensembles de critères et d’alternatives. En outre, nous avons examiné la dépendance entre les critères et les alternatives. Dans ce cas, l'incertitude au niveau des évaluations est donnée sous forme de masses conditionnelles. Une autre partie de nos travaux répond aux critiques concernant la procédure de comparaison. Pour cela, nous avons proposé deux approches. La première technique d’élicitation des jugements de l’expert est fondée sur des distributions de masses, alors que la seconde s'appuie sur des relations de préférence. Dans ce cadre, nous avons introduit un modèle qui permet de générer des distributions de masse quantitatives à partir des relations de préférence. Ainsi, nous avons développé une méthode multicritères qui permet d'imiter le raisonnement humain. Cette méthode produit des résultats meilleurs et plus robustes que les approches de la littérature. / Multi-criteria decision making is the study of identifying and choosing alternatives to find the best solution based on different criteria and considering the decision makers’ expectations. However, the expert assessments are sometimes expressed imperfectly. Belief function theory can then provide more flexible and reliable tools to manage different types of imperfection. Thus, in this thesis, we are interested in multi-criteria decision making in an uncertain framework by extending the Analytic Hierarchy Process (AHP) method to the belief function framework. After presenting the theoretical foundations of the AHP method, we proposed an approach that reduces the number of pair-wise comparisons by judging subsets of criteria and alternatives. In addition, we examined the dependence between the criteria and alternatives. In this case, the uncertainty is given in terms of conditional mass distributions. Another part of the work provides critical concerning the pair-wise comparison process. For this purpose, we proposed two approaches. The first expert judgment elicitation method is based on mass distributions, while the second one is based on preference relations. In this context, we have introduced a model that is able to generate quantitative mass distributions from preference relations. Thus, we have developed a multi-criteria decision making method that imitates human reasoning. This method gives better and more robust results than existing approaches.

Submitted by Nadir Basilio (nadirsb@uninove.br) on 2016-06-01T14:36:20Z No. of bitstreams: 1 Jose Luiz Rodrigues Junior.pdf: 1816384 bytes, checksum: f83b0cfa9558fadd55f06d3f851584a9 (MD5) / Made available in DSpace on 2016-06-01T14:36:20Z (GMT). No. of bitstreams: 1 Jose Luiz Rodrigues Junior.pdf: 1816384 bytes, checksum: f83b0cfa9558fadd55f06d3f851584a9 (MD5) Previous issue date: 2015-06-17 / In current data centers, processing routines are scheduled to perform in a given period of time and, in case of delay, make it impossible to conduct the activities of everyday life of the various sectors of the company. Even with modern servers, due to the large volume of data to be processed, it is possible that certain computers are overloaded causing a drop in performance, a longer time to implement and consequently delays in the delivery of results. In this case, alternative scenarios can be created to sequence the tasks again. This work aimed to apply the multi-criteria decision analysis method on the results of the simulation of alternative scenarios for sequencing tasks on computers in a datacenter, in order to overload the resolution of problems. To achieve this purpose have been developed simulation models of task sequencing scenarios and replacement of computer overloaded. The analysis of simulation results was made based on three criteria, namely the Total Processing Time (makespan), the Total delay time, and the number of Delayed Tasks. Subsequently, the results were submitted to analysis method of AHP multicriteria decision (Analitycal Hierarchy Process), allowing you to choose the best setting according to established criteria. It was concluded that the modeling and computer simulation, combined with multi-criteria decision analysis method, can aid in decision making, as it enables sequencing to identify the best solution possible alternative scenarios in front of a computer overload situations. / Nos atuais Datacenters, as rotinas de processamento são programadas para executar em determinado período de tempo e, em caso de atraso, impossibilitar a condução das atividades do dia a dia dos diversos setores da empresa. Mesmo com os modernos servidores, devido ao grande volume de dados para serem processados, é possível que determinados computadores sejam sobrecarregados provocando uma queda em seu desempenho, um tempo maior para a execução e, consequentemente, atrasos na entrega dos resultados. Nesse caso, cenários alternativos podem ser criados para sequenciar novamente as tarefas. Assim, este trabalho teve por objetivo aplicar o método de análise de decisão multicritério nos resultados da simulação de cenários alternativos para o sequenciamento de tarefas em computadores de um Datacenter, visando a resolução para problemas de sobrecarga. Para atingir esse propósito, foram desenvolvidos modelos de simulação de cenários de sequenciamento de tarefas e substituição do computador com sobrecarga. A análise dos resultados da simulação foi realizada considerando três critérios, a saber: o Tempo Total de Processamento (makespan), o Tempo Total de Atraso, e o Número de Tarefas Atrasadas. Posteriormente, os resultados foram submetidos ao método de análise de decisão multicritério AHP (Analitycal Hierarchy Process), permitindo escolher o melhor cenário segundo os critérios estabelecidos. Concluiu-se que a modelagem e simulação computacional, aliada ao método de análise de decisão multicritério, pode auxiliar na tomada de decisão, uma vez que possibilita identificar a melhor solução de sequenciamento em cenários alternativos possíveis diante de situações de sobrecarga de um computador.

This thesis holistically examines the potential for tidal stream turbine (TST) integration to displace diesel generated electricity in remote coastal First Nations communities within the Marine Plan Partnership for the North Pacific Coast region of British Columbia. This thesis utilizes a combination of spatial analysis (GIS Multi-Criteria Decision Analysis) to identify sites; stakeholder engagement to assess TST suitability, bridge knowledge gaps, and understand desired characteristics of community energy systems; and Levelized Cost of Energy (LCOE) analyses for existing diesel and externality included scenarios along with potential TST costs in a candidate community. Results illustrate the need for information within these communities, from resource quantification to characteristics of renewable energy technologies and system feasibility; self-sufficiency as being the primary transition driver; and funding/human resource capacity as being substantial barriers. Within the study region ≈89.8 km2 of feasible resource was identified, with ≈22 km2 of potentially suitable tidal resource in proximity to nine communities. The COVID-19 pandemic resulted in difficulties contacting and arranging interviews with the most suitable communities. Driven by the holistic research mandate requiring community stakeholder engagement to occur in tandem with the economic analyses, Queen Charlotte Village and Skidegate Landing on Haida Gwaii were chosen as the candidate communities, despite not being the most suitable identified communities. The community interviews revealed TSTs as being an acceptable renewable energy technology. Furthermore, the identified site in Skidegate Inlet (SI) was found to have favourable Marine Spatial Planning (MSP) for TST development. Existing diesel generation carries a LCOE of $0.63/kWh, being $0.08-0.14 more per kWh than the literature cited LCOE range for TSTs. The LCOE for CO2 equivalent externalities at current carbon tax prices was found to be an additional $0.02/kWh. Despite having a technically viable peak spring current speed, the SI site was financially unviable for 284 kW of rated capacity across all diesel LCOE scenarios driven by capacity factor (1.62%), high cabling costs (approximately one third of capital costs), and outdated data/assumptions within the Natural Resources Canada Tidal Project Cost Estimation tool used in the tidal LCOE calculations. This work contributes to the progression of tidal energy development on BCs coast along with demonstrating the utility of holistic assessment frameworks for RETs across environmental, social, and economic considerations. The results of this thesis can inform existing MSP efforts in the Marine Plan Partnership for the North Pacific region and the framework developed can be built upon and altered for global use in pursuit of sustainable energy transitions. / Graduate

The doctoral thesis deals with the interdisciplinary issue of variants evaluation from real estate engineering, multi-criteria analyses and geographic information systems, and represents the technological ways of the visual aspect related to mutual spatial relations of real estates. The thesis describes the design and verification of methodology dealing with the use of GIS technology in real estate engineering. The primary element of the methodology is the locality as a fundamental determinant of the real estate market objects to which strictly applies a unique characteristic of spatial information. The object location as such is defined by a large number of criteria that need to be spatially analysed. For the needs of spatial analysis was chosen combination of GIS technology with multi-criteria methods (MCDA) which evaluate variants of the problem. Objective determination of a suitable combination of weighting methods and multi-criteria methods is part of the methodology. An objective determination should lead to a reduction in the human factor risk by determining preferences and variants. The proposed procedures are validated on case studies which were dealt with in specific projects. This methodology should be beneficial not only for the criteria evaluation of price comparison in real estate engineering but also for several areas of multi-criteria decision making in terms of space and location-related data.

Cette thèse s'appuie sur deux axes. L'un appliqué traite de la création d'un indicateur dont le but est d'évaluer la gravité attendue des conséquences d'un scénario de pollution accidentelle. J'ai choisi d'utiliser des outils méthodologiques appartenant au domaine de l'aide multi-critères à la décision pour traiter ce premier sujet. Ce problème impliquant plusieurs disciplines scientifiques, j'ai choisi de le diviser en plusieurs sous-problèmes à travers une arborescence de critères. J'ai également impliqué plusieurs experts, notamment en toxicologie et en écologie afin de mieux prendre en compte les aspects liés à ces deux disciplines dans la création de cet indicateur.L'étude des méthodes de tri multicritère effectuée lors des recherches sur le premier axe m'a amené à en proposer une nouvelle que j'ai nommé algorithme du Dominance Based Monte Carlo (DBMC). Cet algorithme a comme particularités de n'être pas fondé sur un modèle et de fonctionner de manière stochastique. Nous avons étudié ses propriétés théoriques, en particulier nous avons démontré qu'en dépit de sa nature stochastique, le résultat de l'algorithme Dominance Based Monte Carlo converge presque sûrement. Nous avons également étudié son comportement et ses performances pratiques à travers un test nommé k-fold cross validation et les avons comparés aux performances d'autres algorithmes d'élicitation des préférences pour le tri multi-critères. / This thesis is based on two main axes. The first one deals with the creation of an indicator that aims at evaluating the expected severity of the consequences of a scenario of accidental pollution. In order to create this methodology ofevaluation, I chose to use methodological tools from multi-criteria decision aiding. So as to deal with the complexity of this problem, i decided to split it into several sub-problems using a hierarchy of criteria, being mainly inspired by the "value focused thinking approach". In this work, I interacted with several experts in toxicology and in ecology in order to betterdeal with every aspect of this problem.While studying several elicitation methods for the multi-criteria sorting problem, I proposed a new one that I named Dominance Based Monte Carlo algorithm (DBMC), which brings me to the secons axis of this thesis. This elicitation algorithm has two main specificities: being model free and a stochastic functionning. In this thesis, we study its theoretical properties. In particular, we prove that despite its stochastic nature, the result of the Dominance Based Monte Carlo algorithm converges almost surely. We also study its practical performances through a test named k-fold validation and we compared these performances to those of other elicitation algorithms for the sorting problem.

This thesis analyses how public decision-makers can rapidly and sustainably decarbonise their regions, considering the challenge that promoting timely decarbonisation represents. The research was divided into three phases and developed using desk studies and interviews with Project Drawdown (PD) experts, Swedish public officials and researchers. In phase one, PD solutions showed a shortcoming in sustainable operationalisation of global decarbonisation solutions. It was found that they alone could not account for sustainability, and that there is dependency on the context of application and on decision-making processes. In phase two, it was found that sustainability could be embedded in decision-making for decarbonisation through decision support. In the Blekinge example case, several challenges were found, for which sustainable decision support was needed. To respond to this challenge, a Decision Support tool (DST) was created, based on multi-criteria decision analysis. This three-step generic tool provides a relevance assessment to prove the suitability of decarbonisation solutions in the given context, a sustainability assessment to address sustainability challenges, and a prioritisation step for strategic decision-making. The tool was validated to be useful by Swedish policymakers and by international experts. This DST has the potential to support policy-making around the world to decarbonise regions rapidly and sustainably.

There has been an increasing relevance of the cultural sector in the economic and social development of different countries. However, this sector continues without much input from multi-criteria decision-making (MDCM) techniques and sustainability analysis, which are widely used in other sectors. This paper proposes an MCDM model to assess the sustainability of a musical institution’s program. To define the parameters of the proposed model, qualitative interviews with relevant representatives of Catalan cultural institutions and highly recognized professionals in the sector were performed. The content of the 2015–2016 season of the ‘Palau de la Música Catalana’, a relevant Catalan musical institution located in Barcelona, was used as a case study to empirically test the method. The method allows the calculation of a season value index (SVI), which serves to make more sustainable decisions on musical season programs according to the established criteria. The sensitivity analysis carried out for different scenarios shows the robustness of the method. The research suggests that more complex decision settings, such as MCDM methods that are widely used in other sectors, can be easily applied to the sustainable management of any type of cultural institution. To the best of the authors’ knowledge, this method was never applied to a cultural institution and with real data. / Universitat Oberta de Catalunya

Multi-Criteria Decision Making (MCDM) problems are often associated with tradeoffs between performances of the available alternative solutions under decision making criteria. These problems become more complex when performances are associated with uncertainty. This study proposes a stochastic MCDM procedure that can handle uncertainty in MCDM problems. The proposed method coverts a stochastic MCDM problem into many deterministic ones through a Monte-Carlo (MC) selection. Each deterministic problem is then solved using a range of MCDM methods and the ranking order of the alternatives is established for each deterministic MCDM. The final ranking of the alternatives can be determined based on winning probabilities and ranking distribution of the alternatives. Ranking probability distributions can help the decision-maker understand the risk associated with the overall ranking of the options. Therefore, the final selection of the best alternative can be affected by the risk tolerance of the decisionmakers. A Group Decision Support System (GDSS) is developed here with a user-friendly interface to facilitate the application of the proposed MC-MCDM approach in real-world multiparticipant decision making for an average user. The GDSS uses a range of decision making methods to increase the robustness of the decision analysis outputs and to help understand the sensitivity of the results to level of cooperation among the decision-makers. The decision analysis methods included in the GDSS are: 1) conventional MCDM methods (Maximin, Lexicographic, TOPSIS, SAW and Dominance), appropriate when there is a high cooperation level among the decision-makers; 2) social choice rules or voting methods (Condorcet Choice, Borda scoring, Plurality, Anti-Plurality, Median Voting, Hare System of voting, Majoritarian iii Compromise ,and Condorcet Practical), appropriate for cases with medium cooperation level among the decision-makers; and 3) Fallback Bargaining methods (Unanimity, Q-Approval and Fallback Bargaining with Impasse), appropriate for cases with non-cooperative decision-makers. To underline the utility of the proposed method and the developed GDSS in providing valuable insights into real-world hydro-environmental group decision making, the GDSS is applied to a benchmark example, namely the California‘s Sacramento-San Joaquin Delta decision making problem. The implications of GDSS‘ outputs (winning probabilities and ranking distributions) are discussed. Findings are compared with those of previous studies, which used other methods to solve this problem, to highlight the sensitivity of the results to the choice of decision analysis methods and/or different cooperation levels among the decision-makers