This study is conducted with the aims to develop a new ranking method for multi-criteria decision making problem with conflicting criteria. Such a problem has a set of Pareto solutions, where the act of improving a value of one solution will result in depreciating some of the others. Thus, in this type of problem, there is no unique solution. However, out of many available options, the Decision Maker eventually has to choose only one solution. With this problem as the motivation, the current study develops a compromise ranking algorithm, namely a trade-off ranking method. The trade-off ranking method able to give a trade-off solution with the least compromise compared to other choices as the best solution. The properties of the algorithm are studied in the thesis on several test cases. The proposed method is compared against several multi-criteria decision making methods with ranking based on the distance measure, which are the TOPSIS, relative distance and VIKOR. The sensitivity analysis and uncertainty test are carried out to examine the methods robustness. A critical criteria analysis is also done to test for the most critical criterion in a multi-criteria problem. The decision making method is considered further in a fuzzy environment problem where the fuzzy trade-off ranking is developed and compared against existing fuzzy decision making methods.

Este trabalho trata da logística envolvida em operações de resposta a desastres, com foco na entrega final de suprimentos destinados a ajudar vítimas. Seu propósito é investigar os objetivos pertinentes ao planejamento do transporte da carga e encontrar uma metodologia para definir estratégia que sirva à tomada de decisão em campo. Para tanto, primeiramente identifica-se os objetivos adotados em modelos de Pesquisa Operacional para a tarefa em questão, através da análise de conteúdo das publicações pertinentes. Então, a abordagem do Pensamento Focado em Valores é utilizada para estruturar o problema. Finalmente, o método Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER) é empregado na construção de um modelo de Análise da Decisão Multicritério (ADM), com consulta a um profissional experiente da área humanitária e aproveitando a análise da literatura previamente realizada. Neste processo, são elaboradas e avaliadas seis alternativas para a tomada de decisão condizentes com os valores da comunidade humanitária. Os resultados obtidos mostram que existe incompatibilidade entre os critérios de desempenho identificados nas publicações existentes e os objetivos perseguidos pelo Tomador da Decisão (TD) real. De acordo com o modelo construído, o atendimento de prioridades e a manutenção da sustentabilidade da operação são os objetivos que devem ser levados em conta para planejar a entrega de carga em pós-desastre, sendo que o custo e a equidade da distribuição não devem ser considerados. Conclui-se que o método adotado é útil à definição destes critérios e também ao desenvolvimento de estratégias que resultem em distribuições de ajuda melhores, aos olhos do próprio TD. Desta forma, ressalta-se que este trabalho contribui à área da Logística Humanitária com a investigação dos objetivos, assim como ao campo da ADM pela formalização dos processos de elaboração de alternativas, além da adição de mais uma aplicação possível ao repertório do método SMARTER. / This study concerns the logistics of disaster response operations, with a focus on final delivery of supplies to victims. The objectives here are to investigate what objectives are pertinent to the transportation-planning task and to find a methodology for choosing a strategy that aids decision-making on the field. For achieving these, a content analysis of Operations Research models is done, allowing the identification of such objectives, from which the problem is structured using a Value-Focused Thinking approach. Subsequently, the Simple Multi-Attribute Rating Exploiting Ranks (SMARTER) is employed to build a Multi-Criteria Decision Analysis (MCDA) model, consulting an experienced humanitarian professional and taking into account the results from the previous analysis. Throughout this process, six alternatives for making decisions are designed and evaluated based on the objectives defined. Findings are that there is incompatibility between performance criteria identified in the literature and objectives pursued by a real Decision Maker (DM). From the model presented by this thesis, one concludes that satisfying priorities and sustaining the response operation are the objectives to be taken into account when drawing an aid distribution plan. It also follows that the methodology adopted here is useful to defining such performance criteria and to develop strategies that result in better outcomes, as judged by the DM. Therefore, this study contributes to Humanitarian Logistics research area by casting a light on the objectives of a post-disaster task, and to the MCDA field by formalizing the process of designing alternatives for complex problems, besides adding a new application of SMARTER to its repertory.

In the era of "big data revolution," marked by an exponential growth of information, extracting value from data enables analysts and businesses to address challenging problems such as drug discovery, fraud detection, and earthquake predictions. Multi-Criteria Decision Support (MCDS) queries are at the core of big-data analytics resulting in several classes of MCDS queries such as OLAP, Top-K, Pareto-optimal, and nearest neighbor queries. The intuitive nature of specifying multi-dimensional preferences has made Pareto-optimal queries, also known as skyline queries, popular. Existing skyline algorithms however do not address several crucial issues such as performing skyline evaluation over disparate sources, progressively generating skyline results, or robustly handling workload with multiple skyline over join queries. In this dissertation we thoroughly investigate topics in the area of skyline-aware query evaluation. In this dissertation, we first propose a novel execution framework called SKIN that treats skyline over joins as first class citizens during query processing. This is in contrast to existing techniques that treat skylines as an "add-on," loosely integrated with query processing by being placed on top of the query plan. SKIN is effective in exploiting the skyline characteristics of the tuples within individual data sources as well as across disparate sources. This enables SKIN to significantly reduce two primary costs, namely the cost of generating the join results and the cost of skyline comparisons to compute the final results. Second, we address the crucial business need to report results early; as soon as they are being generated so that users can formulate competitive decisions in near real-time. On top of SKIN, we built a progressive query evaluation framework ProgXe to transform the execution of queries involving skyline over joins to become non-blocking, i.e., to be progressively generating results early and often. By exploiting SKIN's principle of processing query at multiple levels of abstraction, ProgXe is able to: (1) extract the output dependencies in the output spaces by analyzing both the input and output space, and (2) exploit this knowledge of abstract-level relationships to guarantee correctness of early output. Third, real-world applications handle query workloads with diverse Quality of Service (QoS) requirements also referred to as contracts. Time sensitive queries, such as fraud detection, require results to progressively output with minimal delay, while ad-hoc and reporting queries can tolerate delay. In this dissertation, by building on the principles of ProgXe we propose the Contract-Aware Query Execution (CAQE) framework to support the open problem of contract driven multi-query processing. CAQE employs an adaptive execution strategy to continuously monitor the run-time satisfaction of queries and aggressively take corrective steps whenever the contracts are not being met. Lastly, to elucidate the portability of the core principle of this dissertation, the reasoning and query processing at different levels of data abstraction, we apply them to solve an orthogonal research question to auto-generate recommendation queries that facilitate users in exploring a complex database system. User queries are often too strict or too broad requiring a frustrating trial-and-error refinement process to meet the desired result cardinality while preserving original query semantics. Based on the principles of SKIN, we propose CAPRI to automatically generate refined queries that: (1) attain the desired cardinality and (2) minimize changes to the original query intentions. In our comprehensive experimental study of each part of this dissertation, we demonstrate the superiority of the proposed strategies over state-of-the-art techniques in both efficiency, as well as resource consumption.

<p>U ovom radu predložen je model za vrednovanje i izbor dobavljača koji je razmatran u vi&scaron;e od deset različitih proizvodnih oblasti. Model se sastoji od dvadeset kvantitavnih i kvalitativnih kriterijuma koji su primenom fuzzy AHP (Analitičko Hijerarhijski Proces) metode, a na osnovu ocenjivanja menadžera proizvodnih kompanija smanjeni na ukupno devet. Verifikacija datog modela predstavljena je kroz vrednovanje i izbor dobavljača u tri kompanije koje se bave različitom delatno&scaron;ću. Pored doprinosa koji se ogleda u primenjivosti razvijenog modela u različitim lancima snabdevanja, veliki doprinos ovog rada je razvoj novih pristupa u oblasti vi&scaron;ekriterijumskog odlučivanja koji može biti primenjen u svim lancima snabdevanja, naročito u procesima u kojima vladaju neizvesnosti i nejasnoće &scaron;to je detaljno obja&scaron;njeno kroz rad.</p> / <p>In this paper, a model for evaluation and supplier selection has been<br />proposed, which has been considered in more than ten different production<br />areas. The model consists of twenty quantitative and qualitative criteria which<br />are reduced to a total of nine by the application of the fuzzy AHP (Analytic<br />Hierarchy Process) method and the assessment of managers in production<br />companies. The verification of the given model is presented through the<br />evaluation and supplier selection in three companies that deal with different<br />activities. In addition to the contribution reflected in the applicability of the<br />developed model in various supply chains, the great contribution of this<br />paper is the development of new approaches in the field of multi-criteria<br />decision making that can be applied in all supply chains, especially in<br />processes that are subject to uncertainty and vagueness, which is explained<br />in detail through the work.</p>

The requirements for public utility systems in the United States of America have grown enormously over the years triggering a tremendous shortage for space available to public utilities on and within transportation right-of-ways (ROW). Overcrowding and improper location of utilities has resulted in problems such as, damage to infrastructure, traffic accidents and, interruption of service to customers. The project titled, "Optimal Placement of Utilities within FDOT Right-of-Way", sponsored by the Florida Department of Transportation (FDOT), and currently being investigated at the University of South Florida, presents a decision-making heuristic aimed at developing a better utility placement allocation system (Kranc et. al) [6]. Working in accordance with the guidelines of safety, relocation, and clearance for utility placement set by the American Association of State Highway and Transportation Officials organization (AASHTO), the heuristic finds suitable locations for the utilities in ROW corridors. However, a model being used to advocate a practice having large social and economical impacts is more likely to play the role of generic evidence in a trial, whose weight must ultimately be established by a 'jury'. The question being addressed to the system must be scrutinized carefully, and the formal structure updated iteratively until it proves capable of providing an answer to the given question. A good sensitivity analysis can provide this generic quality assurance to the model and help demonstrate the worthiness of the model itself. This thesis is a quantitative and qualitative sensitivity analysis of the abovementioned heuristic. The analysis is conducted in two parts, 1. The 'Model Factor Sensitivity Analysis', with the objective of assessing the uncertainties associated with the modeling of the heuristic. This analysis focuses primarily on providing an evaluation of the confidence in the heuristic and its predictions by analyzing the influences that variations in the input factors have on the outputs of the utility cost assessment models and the final output of the heuristic itself. Variance based sensitivity indices derived from Sobol' sensitivity indices [42] are used here for this purpose. 2. The 'Model Output Evaluation and Enhancement' study, which initially focuses on understanding / evaluating the complexities of the discrete step, cost optimization procedure used in the heuristic and later, based on certain observed shortcomings and problems develops an enhancement, the Ideal Configuration Selector (ICS) to be implemented with the heuristic. The ICS addresses all the problems of the heuristic with the help of experimental speedup, positional sensitivity and refinement tools and employs a multi criterion evaluation technique for utility configuration assessment to provide substantiation to the outputs determined by the heuristic.

The Pre-Project Phase of building construction manages the communication between client organization, user groups and designers. Disconnects and miscommunication in this phase may result in a product that does not fulfill the expectations of the parties involved. It is expected that the adoption of more formal methods can streamline the communication and improve its precision. Based on a literature review, a triage of methods is introduced: (a) a method for initial criteria management, supported by the EcoProP software (developed by VTT in Finland); (b) a method to rationalize and manage criteria in relation to the design organizational instruments, supported by the QFD ProP software (developed by VTT in Finland); (c) a method that supports multi criteria decision making, supported by a range of commercially available software tools. In order to assess the effectiveness of these tools they have been applied in the specific case of Pre-Project Phase of a healthcare facility. A Case Study on a concrete discrete decision problem is dealt with. It concerns the choice between a central medication room and patient room dispenser closets (also known as Nurservers). The Nurservers Case Study is used to evaluate the applicability of the proposed criteria gathering, ranking and decision methods in the Pre-Project Phases daily practices. The claim that these rational methods increase efficiency, precision and satisfaction of the parties involved in this phase is investigated. The thesis evaluates how the introduction of rational methods benefits the communication between stakeholders.

Search and Rescue (SAR) operations aim at finding missing objects with minimum time in a determined area. There are fundamentally two problems in these operations. The first problem is assessing highly reliable probability distribution maps, and the second is determining the search pattern that sweeps the area from the air as fast as possible. In this study, geographic information systems (GIS) and multi criteria decision analysis (MCDA) are integrated and a new model is developed based upon Search Theory in order to find the position of the missing object as quickly as possible with optimum resource allocation. Developed model is coded as a search planning tool for the use of search and rescue planners. Inputs of the model are last known position of the missing object and related clues about its probable position. In the developed model, firstly related layers are arranged according to their priorities based on subjective expert opinion. Then a multi criteria decision method is selected and each data layer is multiplied by a weight corresponding to search expert&rsquo / s rank. Then a probability map is established according to the result of MCDA methods. In the second phase, the most suitable search patterns used in literature are applied based on established probability map. The developed model is a new approach to shortening the time in SAR operations and finding the suitable search pattern for the data of different crashes.

Many countries around the world integrated Renewable Energy Systems (RES) in their future energy plans in order to reduce negative impacts of fossil fuel consumption on the environment. However, RES may as well cause various environmental problems which are mostly related with the geographic locations of these facilities. The aim of this thesis is to create a Geographic Information System-based methodology for evaluating alternative locations for wind, solar and hybrid power plants by using fuzzy multi-criteria decision making. Environmental objectives and economical feasibility criteria for wind and solar systems are identified through Turkish legislations, previous studies, and interviews with General Directorate of Electrical Power Resources Survey and Development. Individual satisfaction degrees for each alternative location with respect to the identified environmental objectives and economical feasibility criteria are calculated using fuzzy set theory tools. Then these individual satisfaction degrees are aggregated into overall performance indexes which are used to determine priority maps for wind and solar energy generation facilities. Finally, maps of priority sites for wind and solar energy systems are overlaid to identify suitable locations for hybrid wind-solar energy systems. The proposed methodology is applied on a case study area composed of USak, Aydin, Denizli, Mugla, and Burdur provinces.

In this study, for the well-known Analytic Hierarchy Process (AHP) method a new approach to interval priority weight generation from interval comparison matrix is proposed. This method can be used for both inconsistent and consistent matrices. Also for the problems having more than two hierarchical levels a synthesizing heuristic is presented. The performances of the methods, interval generation and synthesizing, are compared with the methods that are already available in the literature on randomly generated matrices.

The purpose of this study is to develop a geotechnical microzonation model regarding the suitability of the residential areas in Yenisehir (Bursa, Turkey), which is a currently developing settlement area in a seismically active region. For this purpose, soil properties and dynamic soil behaviors of the study area were assessed. Soil classification, soil amplification, natural soil predominant period, resonance phenomena and liquefaction potential of the study area were evaluated using borehole data and microtremor measurements. The raw data obtained from the previous studies carried out at Yenisehir were used for these assessments. The liquefaction potential for the study area was evaluated both in two-dimensional planimetric and three-dimensional volumetric assessments. Two geotechnical microzonation maps were produced for the study area according to the surface damage due to liquefaction (according to two different methods), soil amplification and distance to streams maps / by using Geographical Information Systems (GIS) based Multi-Criteria Decision Analysis. The weight values were assigned to the layers using Analytical Hierarchical Process method by pairwise comparisons. Evaluating geotechnical microzonation maps produced, the safest areas were found on the northern sites of the study area. The most critical areas were found to be in the middle and the southeast parts of the study area.