Background and Motivation Unlike what is common in Europe and the rest of the world, Norway has traditionally met most of its stationary energy demand (including heating) with electricity, because of abundant access to hydropower. However, after the deregulation of the Norwegian electricity market in the 1990s, the increase in the electricity generation capacity has been less than the load demand increase. This is due to the relatively low electricity prices during the period, together with the fact that Norway’s energy companies no longer have any obligations to meet the load growth. The country’s generation capacity is currently not sufficient to meet demand, and accordingly, Norway is now a net importer of electricity, even in normal hydrological years. The situation has led to an increased focus on alternative energy solutions. It has been common that different energy infrastructures – such as electricity, district heating and natural gas networks – have been planned and commissioned by independent companies. However, such an organization of the planning means that synergistic effects of a combined energy system to a large extent are neglected. During the last decades, several traditional electricity companies have started to offer alternative energy carriers to their customers. This has led to a need for a more comprehensive and sophisticated energy-planning process, where the various energy infrastructures are planned in a coordinated way. The use of multi-criteria decision analysis (MCDA) appears to be suited for coordinated planning of energy systems with multiple energy carriers. MCDA is a generic term for different methods that help people make decisions according to their preferences in situations characterized by multiple conflicting criteria. The thesis focuses on two important stages of a multi-criteria planning task: - The initial structuring and modelling phase - The decision-making phase The Initial Structuring and Modelling Phase It is important to spend sufficient time and resources on the problem definition and structuring, so that all disagreements among the decision-maker(s) (DM(s)) and the analyst regarding the nature of the problem and the desired goals are eliminated. After the problem has been properly identified, the next step of a multi-criteria energy-planning process is the building of an energy system model (impact model). The model is used to calculate the operational attributes necessary for the multi-criteria analysis; in other words, to determine the various alternatives’ performance values for some or all of the criteria being considered. It is important that the model accounts for both the physical characteristics of the energy system components and the complex relationships between the system parameters. However, it is not propitious to choose/build an energy system model with a greater level of detail than needed to achieve the aims of the planning project. In my PhD research, I have chosen to use the eTransport model as the energy system model. This model is especially designed for planning of local and regional energy systems, where different energy carriers and technologies are considered simultaneously. However, eTransport can currently provide information only about costs and emissions directly connected to the energy system’s operation. Details about the investment plans’ performance on the remaining criteria must be found from other information sources. Guidelines should be identified regarding the extent to which different aspects should be accounted for, and on the ways these impacts can be assessed for each investment plan under consideration. However, it is important to realize that there is not one solution for how to do this that is valid for all kind of local energy-planning problems. It is therefore necessary for the DM(s) and the analyst to discuss these issues before entering the decision-making phase. The Decision-Making Phase Two case studies have been undertaken to examine to what extent the use of MCDA is suitable for local energy-planning purposes. In the two case studies, two of the most well-known MCDA methods, the Multi-Attribute Utility Theory (MAUT) and the Analytical Hierarchy Process (AHP), have been tested. Other MCDA methods, such as GP or the outranking methods, could also have been applied. However, I chose to focus on value measurement methods as AHP and MAUT, and have not tested other methods. Accordingly, my research cannot determine if value measurement methods are better suited for energy-planning purposes than GP or outranking methods are. Although all MCDA methods are constructed to help DMs explore their ‘true values’ – which theoretically should be the same regardless of the method used to elicit them – our experiments showed that different MCDA methods do not necessarily provide the same results. Some of the differences are caused by the two methods’ different ways of asking questions, as well as the DMs’ inability to express clearly their value judgements by using one or both the methods. In particular, the MAUT preference-elicitation procedure was difficult to understand and accept for DMs without previous experience with the utility concept. An additional explanation of the differences is that the external uncertainties included in the problem formulation are better accounted for in MAUT than in AHP. There are also a number of essential weaknesses in the theoretical foundation of the AHP method that may have influenced the results using that method. However, the AHP method seems to be preferred by DMs, because the method is straightforward and easier to use and understand than the relatively complex MAUT method. It was found that the post-interview process is essential for a good decision outcome. For example, the results from the preference aggregation may indicate that according to the DM’s preferences, a modification of one of the alternatives might be propitious. In such cases, it is important to realize that MCDA is an iterative process. The post-interview process also includes presentation and discussion of results with the DMs. Our experiments showed that the DMs might discover inconsistencies in the results; that the results do not reflect the DM’s actual preferences for some reason; or that the results simply do not feel right. In these cases, it is again essential to return to an earlier phase of the MCDA process and conduct a new analysis where these problems or discrepancies are taken into account. The results from an MAUT analysis are usually presented to the DMs in the form of expected total utilities given on a scale from zero to one. Expected utilities are convenient for ranking and evaluation of alternatives. However, they do not have any direct physical meaning, which quite obviously is a disadvantage from an application point of view. In order to improve the understanding of the differences between the alternatives, the Equivalent Attribute Technique (EAT) can be applied. EAT was tested in the first of the two case studies. In this case study, the cost criterion was considered important by the DMs, and the utility differences were therefore converted to equivalent cost differences. In the second case study, the preference elicitation interviews showed, quite surprisingly, that cost was not considered among the most important criteria by the DMs, and none of the other attributes were suitable to be used as the equivalent attribute. Therefore, in this case study, the use of EAT could not help the DMs interpreting the differences between the alternatives. Summarizing For MCDA to be really useful for actual local energy planning, it is necessary to find/design an MCDA method which: (1) is easy to use and has a transparent logic; (2) presents results in a way easily understandable for the DM; (3) is able to elicit and aggregate the DMs' real preferences; and (4) can handle external uncertainties in a consistent way.

Along with the rapid expansion of information technology and the urgent demand of Decision Support System, only in a few years, data warehouse have been converting absolute theory into practical technology. More and more enterprises have been plunging into the data warehouse system for supporting business process and decision. Data warehouse system does transfer big data of enterprise to useful resource or information and will not impact current history data. The data warehouse depends on enterprise various demands and plays the role of Decision Support System. It is the reason that enterprise pays attention and positive investment. This paper identifies as a set of evaluating criteria on the literature review and consults the expert to decide vendor level, design the questionnaire and retrieve weight. At last the paper uses the real case evaluating data warehouse system by ELECTRE I. The result of this study can not only contribute to the understanding of functionalities of a data warehouse system but can provide a practical guideline for selection of a data warehouse system.

The use of goal programming in various real-world areas - including resource allocation, engineering, agriculture and other applications - has increased a lot in the past few years. The aim of this dissertation is to investigate goal programming approaches in determining prices. Various aspects of price determination - such as cosls, existing prices, competitors' prices, volume change due to price change and other aspects are incorporated in the model in order to suggest reasonable and realistic prices. Taking just these factors into account will not completely solve the problem, as there are usually certain goals that the decision maker would like to achieve. For example, the decision maker would probably like to attain an acceptable pre-specified minimum profit level without adjusting current prices too much whilst keeping prices competitive to insure that customers are not lost in the process of change. In this study, a goal programming model is developed for the determining of products' prices with consideration of these goals. The model makes provision for the change in demand due to the change in prices. / Mini-dissertation (M.Com. (Computer Science))--North-West University, Potchefstroom Campus, 2007.

Transformations of the various agricultural systems have been taking place in the coastal zone of Bangladesh. While some farmers continue to follow traditional practices, in recent years, others have become involved in massive shrimp cultivation, shrimp-rice cultivation, a rice-based improved agricultural system or a shrimp-rice-vegetable integrated system. All these types of agriculture are being practiced under highly vulnerable environmental conditions. The long-term livelihood, food security and adaptation of the coastal people largely depend on the sustainability of these agricultural practices. In this context, assessing the level of sustainability is extremely important and will be essential for developing future policy options in Bangladesh. This study attempts to examine the sustainability of agricultural practices in the coastal region of Bangladesh. A field study was carried out in 2011 in five villages of five upazilas in the mature and active delta areas of the country. The data were collected through in-depth questionnaire surveys, focus groups discussions, field observation, key informants and secondary materials. A comprehensive suite of indicators was developed considering productivity, efficiency, stability, durability, compatibility and equity of the coastal agriculture. The categories and the indicators were weighted using Multi-Criteria Decision Analysis (MCDA) to measure the sustainability level of five study sites. The integrated agricultural system (shrimp-rice-vegetable) of Dumuria appeared to be the most sustainable system among agricultural practices, and other integrated systems (rice-based improved agricultural system) of Kalaroa were also found to show a good level of sustainability. The massive shrimp cultivation system of Shyamnagar and Kaliganj appears to be least sustainable. A traditional agriculture system with some improved methods followed in Bhola Sadar also performed in a satisfactory manner, but there were limitations in terms of its location in the active delta. The level of the sustainability measured in this study allows for a comparison among agricultural practices of the five study sites. The information generated from the study may be used in formulating policies for this part of the country. Measuring agricultural sustainability in this way produces a useful summary of sustainability issues and also provides some vital learning experiences. A holistic and interdisciplinary approach is attempted in this study for assessing and comparing the sustainability level of coastal agricultural systems. It has the potential to become useful as one of the frameworks for sustainability assessment. / Thesis (Master, Environmental Studies) -- Queen's University, 2012-09-28 15:08:18.847

The use of goal programming in various real-world areas - including resource allocation, engineering, agriculture and other applications - has increased a lot in the past few years. The aim of this dissertation is to investigate goal programming approaches in determining prices. Various aspects of price determination - such as cosls, existing prices, competitors' prices, volume change due to price change and other aspects are incorporated in the model in order to suggest reasonable and realistic prices. Taking just these factors into account will not completely solve the problem, as there are usually certain goals that the decision maker would like to achieve. For example, the decision maker would probably like to attain an acceptable pre-specified minimum profit level without adjusting current prices too much whilst keeping prices competitive to insure that customers are not lost in the process of change. In this study, a goal programming model is developed for the determining of products' prices with consideration of these goals. The model makes provision for the change in demand due to the change in prices. / Mini-dissertation (M.Com. (Computer Science))--North-West University, Potchefstroom Campus, 2007.

Telecommunications infrastructure is recognised as the fundamental factor for economic and social development for it is the platform of communication and transaction within and beyond geographical boundaries. It is a necessity for social benefits, growth, connection and competition, more in the rural communities in developing countries. Its acquisition entails great investment, considering the emergence of various technologies and thereby making the selection a critical task. The research described in this thesis is concerned with a comprehensive examination and analytical procedures on the selection of technologies, for rural telecommunications infrastructure. A structured systematic approach is deemed necessary to reduce the time and effort in the decision-making process. A literature review was carried out to explore the knowledge in the areas of Multi-Criteria Decision-Making (MCDM) approaches, with particular focus on the analytical decision processes. The findings indicate that, the Analytic Hierarchy Process (AHP)/AnalyticNetwork Process (ANP) are powerful decision methods capable of modelling such acomplex problem. Primarily, an AHP model is formulated, however, since the problem at hand involves many interactions and dependencies, a more holistic method is required to overcome its shortcomings by allowing for dependencies and feedback within the structure. Hence, the ANP is adopted and its network is established to represent the problem, making way to telecommunications experts to provide their judgements on the elements within the structure. The data collected are used to estimate the relative influence from which the overall synthesise is derived, forming a general ANP model for such a rural telecommunications selection problem. To provide a more wide-ranging investigation regarding selecting a potential rural telecommunications infrastructure, another systematic analysis that utilises a BOCR-based (Benefits, Opportunities, Costs and Risks) ANP was conducted. The obtained results indicate that Microwave technology is the most preferred alternative within the context of the developing countries. Sensitivity analysis was performed to show robustness of the obtained results. This framework provides the structure and the flexibility required for such decisions. It enables decision makers to examine the strengths and weaknesses of the problem, by comparing several technology options, with respect to appropriate gauge for judgement. Moreover, using the ANP, the criteria for such a technology selection task were clearly identified and the problem was structured systematically. A case study was carried out in Libya involving its main telecommunications infrastructure provider to demonstrate how such rural technology selection decisions can be made within a specific developing country's rural area. Based on the results of this case study that were in agreement with the focus group's expectations, it can be concluded that the application of the ANP in the selection of telecommunications technology, is indeed beneficial. In addition, it is believed that telecommunications planners could, by the use of data pertaining to another rural area, utilise the developed model to propose appropriate solutions. If new criteria and/or alternatives emerge to satisfy changing business needs, they can also be included in the ANP model.

Ingeniera Civil Industrial / El presente estudio tiene por objetivo desarrollar e implementar una metodología de priorización de infraestructura hidráulica de riego, de forma que los proyectos de embalses sean estudiados y evaluados en su contexto. Para la elaboración de la herramienta de priorización, se utilizó el método MCDM, el cual corresponde a un enfoque que permite comparar alternativas en base a múltiples atributos y características. Entre los métodos estudiados, se optó por la metodología AHP para determinar los ponderadores, ya que permite incluir, de forma simultánea, características cuantitativas y cualitativas dentro de un mismo modelo. Se desarrolló un modelo con 5 niveles de criterios y subcriterios. En el primer nivel se especifica el objetivo del estudio. En el segundo nivel jerárquico, se consideran los criterios macro, los cuales corresponden a factores de desarrollo y estratégicos. Los criterios de desarrollo están asociados directamente con las características de los proyectos en sí y los criterios estratégicos corresponden a aspectos políticos y administrativos. En el tercer nivel se identifican los factores económico, social y ambiental. El subcriterio económico busca medir las rentabilidades y riesgos del modelo, el subcriterio social incluye los impactos que este tipo de obras tienen sobre las comunidades y el subcriterio ambiental buscar medir el impacto que tienen los embalses en el territorio donde estos se localizan. Este modelo fue aplicado en cuatro proyectos de embalses, a través del cual se obtuvo un Índice Multi-Criterio (IMC), donde a mayor IMC, mayor prioridad tiene el proyecto. Los resultados obtenidos son: en primer lugar el Embalse A, seguido del Embalse C, luego se encuentra el Embalse B y, en último lugar se encuentra el Embalse D. Los resultados muestran que los métodos multicriterio de priorización permiten incluir características cualitativas y cuantitativas de forma simultánea en un modelo. Sin embargo, es necesario perfeccionar este tipo de metodologías en aspectos tales como la selección de criterios, subcriterios e indicadores, de forma que los proyectos de embalses no sean sub o sobre valorados. Adicional a esto, para la correcta aplicación de la metodología multicriterio, es necesario disponer de información actualizada tanto de los proyectos, como de las comunidades y territorio donde estos se localizan.

Municipalities increasingly have less financial resources to spend on implementation of transport strategies and plans. This situation is putting pressure on transport professionals to minimize wasteful expenditure on projects that do not deliver high transport service improvements. As such, the need for efficient, pragmatic decision making on policy direction, infrastructure expenditure, or any transport interventions is becoming very critical. Thus, transport professionals are increasingly in need of tools to help them predict with increased accuracy the outcomes of their intended transport interventions. The City of Cape Town has a Bus Rapid Transport system called MyCiTi. Current MyCiTi operations are incurring losses. The service is kept running on the back of subsidies from the federal government. There is a need for rationalization of the system. However, with strained resources, the interventions on the system have to guarantee improvements. Overemphasis on the ability of MyCiTi BRT service to support transportation during the 2010 soccer world cup event heavily influenced the design of the network. As a result, network appraisal is one area that can be done on the system to identify areas of improvement. In this thesis, decision making support will be demonstrated using a network design appraisal process for the MyCiTi BRT system in Cape Town. The existing MyCiTi network will undergo network improvement using heuristic node insertion technique leading to multiple network scenarios in a modeling environment. Agent-Based demand mobility behavior simulation will be used on each of the network scenarios to come up with network performance indicators. These network performance indicators will be used in the multi-criteria decision analysis (MCDA) model to come up with a ranking of the network scenarios and help in deciding on the optimum network improvement intervention. Overall, findings of this research show the importance of weighting of the performance indicators. Where networks that score well in the performance indicator with the high weights also rank high. In conclusion, the study has demonstrated the importance of decision making support in interventions on complex systems like bus systems. Recommendations on the possible avenues of research stemming from this thesis have also been outlined.

Indiana University-Purdue University Indianapolis (IUPUI) / 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.

The idea of multi-criteria decision making has been around for quite a while. All judgement tasks are potential points of bias introduction. Each judgement task was assessed to identify common biases introduced through an extensive literature review for each task and bias. In several other studies, the distinction is made between cognitive and motivational biases. Cognitive biases are widely studied and well known with mitigations that have been validated. Motivational biases are judgements influenced by the decision maker’s desire for a specific outcome, also referred to as intentional bias, that are hard to correct and received very little testing and exploration. This study tested the techniques that are identified for reducing motivational bias and tested an instrument to identify characteristics within a decision maker that would increase the likelihood that they would be motivationally biased. The results of this study provide a methodology for assessing the susceptibility to motivational biases of the decision makers and provides a framework for reducing the motivational bias within the multi-criteria decision making (MCDM) process using the general steps applicable to all multi-criteria decision analyses. Given that the general steps are used, this methodology is generalizable to any MCDM problem or domain and was found to be reliable and consistent with previous instruments and tools. A summary of the future research to further the explore the methodology and additional techniques for reducing motivational bias is proposed.