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.

Rising levels of urbanization and technological advancements has led to a shift towards dependence on energy consuming devices, machineries, and electrical appliances both for personal and productive use. This has led to higher demand for electricity services and more pressure on power supply facilities. Many sub-Saharan African countries are finding it difficult to cope with the pressure of sustaining energy facilities while providing for the existing demand in a sustainable way. The study focused on the use of Multi Criteria decision models for selecting suitable sites for solar energy infrastructure establishment in Nigeria. The study answered three main questions including 1). What are the various considerations required for the establishment of the suitable land surfaces for solar power plants in Nigeria? 2). What are the spatial extents and estimate the potential land area that can host a renewable energy power plant based on established scenarios? 3). What is the possible contribution of each suitable land area to energy production? Secondary data was acquired for consideration of various criteria including the climatic, environmental, socio economic and geomorphological factors. The various datasets were scaled in order of importance and weighed among each other to produce a suitability map. The output was classified into 5 major suitability classes with certain protected areas totally restricted from the analysis. The suitable areas were labeled 1 to 5 from Unfeasible to Most Feasible. The largest land area was covered by the “Highly Visible” class while the part of the country with highest power production potential was the “Most Feasible” class. The study was able to present a good criteria model that can be useful for countries with similar demography.

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.

Data mining techniques, such as clustering, have become a mainstay in many applications such as bioinformatics, geographic information systems, and marketing. Over the last decade, due to new demands posed by these applications, clustering techniques have been significantly adapted and extended. One such extension is the idea of finding clusters in a dataset that preserve information about some auxiliary variable. These approaches tend to guide the clustering algorithms that are traditionally unsupervised learning techniques with the background knowledge of the auxiliary variable. The auxiliary information could be some prior class label attached to the data samples or it could be the relations between data samples across different datasets. In this dissertation, we consider the latter problem of simultaneously clustering several vector valued datasets by taking into account the relationships between the data samples. We formulate objective functions that can be used to find clusters that are local in each individual dataset and at the same time maximally similar or dissimilar with respect to clusters across datasets. We introduce diverse applications of these clustering algorithms: (1) time series segmentation (2) reconstructing temporal models from time series segmentations (3) simultaneously clustering several datasets according to database schemas using a multi-criteria optimization and (4) clustering datasets with many-many relationships between data samples. For each of the above, we demonstrate applications, including modeling the yeast cell cycle and the yeast metabolic cycle, understanding the temporal relationships between yeast biological processes, and cross-genomic studies involving multiple organisms and multiple stresses. The key contribution is to structure the design of complex clustering algorithms over a database schema in terms of clustering algorithms over the underlying entity sets. / Ph. D.

Signal Replacement decisions are often made based on the experience of the Traffic Engineers. These decisions are made while considering the deployment time of the system, the new technology available, and the performance of the system in the given location. However, there is no set of proper guidelines or methods which can quantify the system replacement decision in large scale projects. This thesis presents a methodology that can be applied to determine optimal migration plans for traffic signal controllers. A Multi-Criteria Decision Making technique has been adopted to evaluate various traffic signal controllers. Various controller manuals were studied and information was obtained from the vendors of the controllers. In addition to that, Geographic Information System (GIS) has been used as a tool to evaluate and identify the areas where the traffic signal controllers have to be replaced first. The study considers the budget constraints and the benefits that can be obtained by the replacement of the controllers. This thesis presents the Methodology adopted for the Migration Plan and a case study implementation on the Northern Virginia Region. Finally it presents the conclusions drawn from the research with insights into the scope for further research. / Master of Science

Approved for public release, distribution is unlimited / Numerous optimization problems involve systems with multiple and often contradictory criteria. Such contradictory criteria have been an issue for marine/naval engineering design studies for many years. This problem becomes more important when one considers novel ship types with very limited or no operational record. A number of approaches have been proposed to overcome these multiple criteria design optimization problems. This Thesis follows the Parameter Space Investigation (PSI) technique to address these problems. The PSI method is implemented with a software package called MOVI (Multi-criteria Optimization and Vector Identification). Two marine/naval engineering design optimization models were investigated using the PSI technique along with the MOVI software. The first example was a bulk carrier design model which was previously studied with other optimization methods. This model, which was selected due to its relatively small dimensionality and the availability of existing studies, was utilized in order to demonstrate and validate the features of the proposed approach. A more realistic example was based on the "MIT Functional Ship Design Synthesis Model" with a greater number of parameters, criteria, and functional constraints. A series of optimization studies conducted for this model demonstrated that the proposed approach can be implemented in a naval ship design environment and can lead to a large design parameter space exploration with minimum computational effort. / Lieutenant Junior Grade, Turkish Navy