This work is dealing with portfolio optimization of stocks available on Czech RM-SYSTEM stock. The optimization is done by multiple criteria decision. In first two chapters there are description of theory of capital market, stock market and stock markets which are on Czech market. The practical part is the main important part of the work. The practical part deals with optimization of portfolio of stocks which are available on Czech stock market. Main goal of this work is to show possibility of creating portfolio of stocks by multiple criteria decision methods.

The aim of this diploma thesis is to formulate recommendations to amend the guideline issued by the Operational Programme Human Resources and Employment. Their subject matter is based on the analysis of decision situations which must be handled by contracting entities in order to successfully find the right contractor. The paper explains the methods of multi criteria decision making which are suitable for use in public procurement. First part describes requirements which are a prerequisite to creating the rational set of evaluation criteria. Theoretical part continues with description of the Public Procurement Act and its recent changes made by amendments. The practical part contains the survey conducted among contracting entities which were supported by operational programme. It is aimed on their approach to organizing competitions and information management. The last part describes the authors proposed changes.

The thesis titled Tesco Potraviny online e-shop contents detailed customer experience based description of functionalities of the Tesco e-shop and some other e-shops competing on the on-line groceries market. Available methods of multi-criteria decision making allowed a platform for comparative analysis of functionalities of Potraviny online, Potraviny domů and Z-market shopping websites. The customer satisfaction survey had been carried out via a multiple choice questionnaire. A proposal for optimalization of the Tesco e-shop, this being the aim of the thesis, has been put together thanks to evaluation of both data collected and multi-criteria analysis being applied. The thesis also provides some subject related information about the Tesco company and looks into how the e-commerce evolves.

The aim of this diploma thesis is to select a suitable task management tool with regards to specific requirements of BNM, s.r.o. company. The list of requirements was compiled based on author's work experience at the particular company. Last but not least the thesis is focused on a solution of identified issues while the theoretical part explains the teamwork theory and team collaboration. Further chapters introduce SaaS oriented software distribution models. The final tool selection is done using a scoring method and WSA (Weighted Sum Product) method belonging to the multi-criteria decision methods category. The decision making proces is further described with a special attention to the selected tool - Asana. None of the considered tools was excluded due to a non-fulfilment of the selection criteria. The main contribution of the thesis is a comparison and evaluation of available task management tools and a selection of a best tool for the one particular company.

<p>Multi-criteria decision making (MCDM) methods have evolved over the past several decades. In today’s world with rapidly growing industries, MCDM has proven to be significant in many application areas. In this study, a decision-making model is devised using reinforcement learning to carry out multi-criteria optimization problems. Learning automata algorithm is used to identify an optimal solution in the presence of single and multiple environments (criteria) using pareto optimality. The application of this model is also discussed, where the model provides an optimal solution to the food, energy, and water systems (FEWS) problem.</p>

Resource efficiency and circular economy (CE) has become increasingly relevant to the Swedish construction company NCC in connection to the plans of demolishing the current head office in Stockholm and building a new head office next to it. NCC wants to investigate how to minimize the negative sustainability implications of bringing down a commercial facility well before its life length has expired, through exploring the possibilities of integrating principles of CE in future planning‐and construction processes. This study seeks to understand how the Swedish construction company NCC could work with decision-making for CE in order to keep their materials in the loop. As the concept of CE is broad there are many options for working with its principles. However, the construction industry is relatively new to these and a list of priorities would therefore be helpful in such an initial phase, as focusing on all would be inefficient and rather daunting. Thus, this study suggests a multi-criteria decision analysis (MCDA) as a tool for decision-making and prioritizing between various approaches to CE. Together with NCC, an MCDA was performed where three different options for working with CE were analysed (Waste as Resource, Circular Design and Circular Business Models). In a focus group, 17 criteria that were relevant to NCC were developed as a basis for analysing the options. These were then defined, scored and weighted to reveal a most preferable option. The MCDA showed that the most preferable approach to CE for NCC is working with circular design, i.e. Design for Deconstruction (DfD), followed closely by measures to increase the rate of reuse and recycling of already existing construction- and demolition waste. However, the sensitivity analysis revealed that if economic criteria received a higher weight, increased reuse and recycling is the most preferable option. MCDA was deemed a helpful decision-making tool for CE principles. While the scoring and weighting is subjective and it is challenging to quantify the criteria, the strength lies in bringing a new and innovative topic on the agenda by gathering key decision-makers in focus groups to discuss and learn. A preliminary study to this thesis was conducted at NCC (Tabrizi, 2015) with the aim of conducting a survey of good examples with regard to development of commercial properties that are designed for flexibility and deconstruction during refurbishment and end‐of‐life. It showed that the challenges relate to the hesitant perception of secondary material, design and construction limitations, the need for material documentation, organization and logistics as well as creating sustainable business models. Key success factors for overcoming these challenges for NCC is working towards better communication and promotion of secondary material through information sharing, building up a knowledge base and internal targets, as well as establishing a consistent work methodology for DfD in order to move NCC towards a circular economy.

In the recent decades, therehave been frequent conflicts between groundwater waterresources and environmentally hazardous activities. Newmethodologies for aiding decision-making in groundwater impactassessment and protection areneeded and in which issues ofincreased awareness, better understanding of the groundwaterresources processes, and validation of predictive mathematicalmodels are addressed. A framework fordecision–aid, based on predictive simulations that a)predicts the environmental impacts b) provides the totaleconomical value c) visualises the impacts and the groundwaterproperties and d) describes the uncertainties in the results isproposed herein. The framework can be applied in environmentalimpact assessments, strategic environmental assessments andprotection and management of water resources. The results ofthe model are used as feedback for determining new scenarios,depending on the required uncertainties, and if the plannedactivity is sustainable, and/or fulfils the legislative andpolicy measures. This framework is applied to a particular casestudy, Nybroåsen, in the south-eastern part of Sweden,where the highway E22 is constructed through the importantglaciofluvial esker aquifer, passing the protection zone of thewater supply for the Kalmar municipality. The impacts from the new highwayand the existing road have been predicted by two-dimensionalphysically based time-variant flow and solute groundwatermodelling. The results, breakthrough curves of contaminantconcentration in wells and maps of concentration distributions,as well as travel times, flow paths, and capture zones forwells determined by particle tracking have been presented. The constructed model of theNybroåsen study area was calibrated by comparing observedand simulated groundwater levels for 15 observation wells forten years of measurements. The model has been evaluated bothgraphically and numerically and the calibration target wasfulfilled for 13 of the 15 observation wells. The model workincludes investigations of the catchment information, a waterbalance study, simulation of the groundwater recharge,consideration of the unsaturated zone by a numerical columnsimulation, and sensitivity analysis. From the sensitivity analysis ofthe flow and transport parameters, it has been shown that theuncertainties are mainly due to the hydraulic conductivity.Comparison of the derived conductivity from the steady-stateautomatic calibration and the time-variant calibration showedthat there are major differences in the derived parameters,which illustrates the importance of a time dependentcalibration over both wet and dry periods and in more than onepoint in the area of interest of the model predictions. In addition, a multi-criteriadecision analysis has been carried out for four roadalternatives (including the new highway E22) and the existingroad in the case study concerned. The multi-criteria decisionaid is applied as an illustration of how it can be used in thestudy area to identify a) interest groups of actors and theirconcerns b) ranking of alternative road scenarios according toactors’preferences and c) coalition groups of actorsi.e.groups that have similar views with regard to theroad alternatives. <b>Keywords:</b>Physically-based groundwater modelling,contamination, flow and solute transport, glaciofluvialdeposits, Nybroåsen, Sweden, and multi-criteriadecision-aid. / NR 20140805

Decision making processes of natural resources for sustainable development are very complex processes that contain large amounts of contradicting criteria and alternatives and/or objectives. Hence efficiency of planning and decision making is highly dependent on the structure of the decision problems. In this re-spect Multi Criteria Decision Aid (MCDA) is the most widely used method. Particularly GIS-based MCDA using the Analytical Hierarchy Process (AHP) is a well-known method in this respect. However, there are interrelationships and interdependences among problems of the real world. As a result, many spatial problems cannot be structured hierarchally because the importance of the criteria determines the importance of the alternatives, and the importance of the alternatives also determines the importance of the criteria. Analytical Network Process (ANP) based MCDA is a new planning and decision making ap-proach that allows the decision problem to be modeled considering feedbacks and interdependence among criteria. This study critically reviews GIS-based MCDA using the AHP method and the ANP based MCDA method and forwarded recommendations for future works. To attain this, practical decision making processes were used of urban form selection for a sustainable development of the Stockholm region. For this purpose literature was reviewed, separate methodologies were developed, criteria were formulated to be analyzed using GIS and SuperDecision software‟s, and finally reasonable results were achieved and separately presented to critically evaluate both the methods and the outcome. This study showed that GIS has the potential to be an important decision aid tool, that the ANP seems to give more realistic results than the GIS-based MCDA method, and that a compact scenario that over time follows already established polycentric pattern would be the best alternative urban form for a sustainable develop-ment of Greater Stockholm.

The average global surface temperature increased by 0.85 °C since 1850 because of irrepressible increase of the concentration of greenhouse gases (GHG). Electricity generation is the primary source of GHG emissions in the United States. Hence, renewable energy sources, which produce a negligible amount of GHG emissions, have gained enormous attention, especially in the electricity generation sector over the past decade. Wind power is the second largest renewable energy source to generate electricity in the United States. Therefore, in this study, a two-stage Data Envelopment Analysis (DEA) is developed to quantitatively evaluate the relative efficiencies of the 39 state's wind power performances for the electricity generation. Both input- and output-oriented CCR (Charnes, Cooper, and Rhodes (1978)) and BCC (Banker, Charnes, and Cooper (1984)) models are applied to pre-determined four input and six output variables. The sensitivity analysis is conducted to test the robustness of the DEA models. Tobit regression models are conducted by using the DEA results for the second stage analysis. The DEA results indicate that more than half of the states operate wind power efficiently. Tobit regression indicates that early installed wind power was more expensive and less productive relative the currently installed wind power. Findings of this study shed some light on the current efficiency assessments of the states and the future of wind energy for both energy practitioners and policy makers.

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