There are three interrelated objectives in a manufacturing facility that are important for the planning and control of a technology comprised of serial production processes. These objectives include plant effectiveness, process effectiveness and a production line-balance between consecutive stages. Plant effectiveness is the degree to which the facility meets its pre-determined plant-level targets. Process effectiveness is the degree to which the production processes meets their pre-determined resource (input) and output targets. The concept of balance exemplifies the degree to which the serial processes exhibit bottlenecks. In this research, all the above three objectives are modeled using a serial-manufacturing goal-programming (SMGP) approach. The results obtained from the SMGP approach are used in conjunction with the traditional DEA analysis to evaluate the overall performance of the plant. This approach is applied to a printed circuit board manufacturing firm for which data has been accumulated for a two-year period. / Master of Science

As the climate change and global warming getting worse, the sustainable development has become the most important issue around the world. There are multiple and interrelated aspects of the sustainable development, including society, economy, and environment. The development of Kaohsiung¡¦s economy was based on heavy industry. However, the high economic growth has severely degraded the environment, such as the environmental capacities have been over the limits due to human pollution. Fortunately, Kaohsiung city government has strived hard to make progress toward sustainable development. For example, the environmental quality has been improved by conducting river renovations and air pollution monitoring. In order to achieve the goal of sustainability in Kaohsiung, the current study has developed the goal programming model which is based on the performances of some key indicators. Such indicator set was carefully selected by referring many domestic and foreign literatures. Meanwhile, the unique natural environment and society of Kaohsiung and statistic data were also considered when selecting the indicator set. Once the indicator set was ready, the regression analysis has been conducted to describe the future trends of each aspect in relation to the indicators. Finally the goal programming model was formulated and the scenario analyses were performed to explore the outcomes under various policies. The results echo the spirit of sustainable development, that is, the administrative policies have to take into account of all aspects, such that the sustainability is achievable.

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Crisp mathematical programming techniques have shortcomings when used for measuring and evaluating achievement of organizational goals in a decision-making environment. Generally, in most real-life situations optimal achievement of multiple goals is rarely possible. In such cases, a compromise achievement of goals that leads to a satisfycing solution rather than an optimal solution bears more relevance. The present research introduces a framework to measure and evaluate the goals of efficiency and effectiveness in a fuzzy environment and is developed using Goal Programming, Data Envelopment Analysis and Fuzzy Set Theory. The proposed framework is called Fuzzy GoDEA and uses surrogate constraints to represent the efficiency and effectiveness goals. DEA type constraints are used to model the efficiency goal. The effectiveness goal is represented by the aggregate efficient contribution of the individual decision-making units toward achievement of the global organizational targets. Concepts of fuzzy set theory and goal programming are used to model the imprecision in goal achievement and the relative importance between goals. Additionally, the concept of minimal operational viability is introduced, though not included in the application due to unavailability of suitable data. The Fuzzy GoDEA framework accommodates crisp input and output data but allows imprecise specification of the aspiration levels for the efficiency and effectiveness goals. The imprecision in goal achievement is allowed through the specification of an interval of acceptable achievement rather than a crisp value. A membership function is defined for each fuzzy constraint associated with the efficiency and effectiveness goals and represents the degree of achievement of that constraint. Further, the Fuzzy GoDEA framework is extended into several variations that (i) allow the assignment of relative importance to the goals of efficiency and effectiveness and (ii) model scenarios where one of the goals of efficiency and effectiveness is crisp and the other fuzzy. The applied component of the research involves the application of the Fuzzy GoDEA framework to a newspaper preprint insertion process (NPIP). Detailed analyses of the results are presented to describe the information available from the Fuzzy GoDEA methodology that can be used in conjunction with conventional DEA analysis to assess and improve the efficiency and effectiveness performance of the NPIP system. / Master of Science

Concerns about energy supply and climate change have been driving companies towards more sustainable manufacturing while they are looking on the economic side as well. One practicable task to achieve sustainability in manufacturing is choosing more sustainable technologies among available technologies. Combination of two functions of ‘Technology Selection’ and ‘Capacity Planning’ is not usually addressed in the research literature. The importance of integrated decisions on technology selection and capacity planning at such strategic level is therefore essentially important. This is supported by justifications in some selected manufacturing areas particularly concerning economies of the scale and accumulated knowledge. Furthermore, manufacturing firms are working in a global competitive environment that is changing in a continuous way. Strategic design of systems under such circumstances requires a carefully modelled approach to deal with the complexity of uncertainties. The overall project aims are to develop an integrated methodological approach to solving the combined ‘technology selection’ and ‘capacity planning’ problems in manufacturing sector. The approach will also incorporate the multi-perspective concept of sustainability, while taking uncertainties into account. A framework consisting of four modules is proposed. Problem structuring module adopts an Ontology method to map the technology mix combinations and to capture input data. ‘Optimisation for Sustainable Manufacturing’ module addresses the optimisation of technology selection and capacity planning decisions in an integrated way using Goal, Mixed Integer Programming method. The model developed takes the multi-criteria aspect of sustainability development into account. Three criteria, namely a) Environmental (e.g. Energy consumption and Emissions), b) Economics, and c) Technical (e.g. Quality) are involved. ‘Normalisation algorithm by comparison with the best value’ method is adopted in this research in order to facilitate a systematic comparison among various criteria. The economic evaluation is based on ‘Life-Cycle Analysis’ approach. The ‘Present Value (PV)’ method is adopted to address ‘Time Value of Money’, while taking both ‘Inflation’ and ‘Market Return’ into account in order to make the proposed model more realistic. A mathematical model to represent the total PV of each technology investment, including both capital and running costs, is developed. ‘Sensitivity Analysis’ module addresses the uncertainty element of the problem. A controlled set of re-optimisation runs, which is guided by a tool coded in Visual Basic for Applications (VBA), is developed to perform intensive sensitivity analyses. It is aimed to deal with the uncertainty element of the problem. Within ‘Solution Structuring’ module, two knowledge structuring schemes, namely Decision Tree and Interactive Slider Diagram, are proposed to deal with the large size of solution sets generated by the “Sensitivity Analysis” module. An innovative, hybrid, Supervised and Unsupervised Machine Learning algorithm is developed to generate a decision tree that aims to structure the solution set. The unsupervised learning stage is implemented using DBSCAN algorithm, while the supervised learning element adopts C4.5 algorithm. The methodological approach is tested and validated using an exemplar case study on coating processes in an automotive company. The case is characterised by three operations, twelve possible technology mix states, both capital budget and environmental limits, and 243 different sensitivity analysis experiments. The painting systems are evaluated and compared based on their quality, technology life-cycle costs, and their potential VOC (Volatile Organic Compounds) emissions into the air.

Complex system is a dynamic open system. Through its interactive variables, we can set up a multiple objectives integrative model, using goal programming technique, to help decision makers making decisions more scientifically. With the outcomes forecasted by complex system, decision makers can make strategy more reasonably and precisely. Adoption of Complex system will make strategy management become more scientific and systematic. Non-profit organizations are star industry of 21-th century. How to manage a non-profit organization well and keep it sustainable forever, management science doesn¡¦t develop a system yet. In this research, we take Kaohsiung as a case study to use complex system in managing non-profit organizations. According to complex system-- multiple objectives integrative model in population, economic, social development resource, environment and sanitation, we can make a systematic plan and forecast to help public policy and budget making. The application shows that the model could find a new way for non-profit organization management and provide a connection in theory and practice.

Abstract The concept of sustainable development in the dynamic operation concerns for the ecosystem¡¦s health, social justice and ideals of responsibility to future generations. From this point of view, the striking levels of economic growth achieved over the past few decades has been accompanied by environmental degradation, which exceeds the carrying capacity of supporting ecosystems in this island. Based on the characteristics of indicators on the Commission on Sustainable Development of United Nations, this research constructs quantitative approaches to evaluate whether the historical data in Taiwan meets the relationship in DSR (Driving-force-State-Response) indicator framework of sustainable development or not. This research also formulates the social-economic-environmental multi-objective programming system to the normative value of sustainable development for planning an optimal strategy path of sustainable development in Taiwan. Moreover, this research also forms a complex system called PREE system, which population (P), resources (R), environment (E) and economy (E) could develop with sustenance, order and coordination, to make policy planning for an overall, comprehensive and systematic mechanism of sustainable development. This research aims at building the indicator system of sustainable development in Taiwan, performing regression analysis for DSR system, finding key indicators of each individual dimension of sustainable development, developing the multi-objective integrated model solved by goal programming for sustainable development, and realizing the scenario analyses with assigned priority change of objective function. The results indicate the historical data in Taiwan meets the relationship in DSR indicator framework of sustainable development. The findings illustrate that the scenario for green income accompanied by the highest priority of environmental quality is optimal under the condition of moderate-driven rate of population growth, if green income per capita is considered to be the core set. On the other hand, the findings also indicate the declining rate of population growth, the depletion of water resource and energy, and the degradation of environment. Some suggestions related to public policies for spreading the international concept of sustainable development and for the balance of socio-environment and natural resource. This research explores that such a process generates as a means for nation to understand what specific actions to take in order to simulate the allocating results of national policy affecting the social, economic and environmental system and to measure progress towards sustainable development.

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.

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.

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