DMO CLASS PROCEEDINGSDate: 05.01.2015 Session: 1 Group No: 1Members: Section: AAishwarya Balasubramaneyam (14008)Nimamachettla Dileep Kumar Reddy (14090)Pradyumna Ramachandran Pillai (14101) SUMMARYFundamentals of the course: to identify and formulate a decision strategy and to obtain a solution to a model. Linear Programming Eg: used in Burger King to minimize costsInteger Programming Eg: used by American Airlines for optimal flight servicesShortest Route Algorithm Eg; used by Sony Corporation for car navigationOptimization: the goal of management science Is to recommend the course of action that is expected to yield the best outcome. The management Science approach is a scientific method of providing a quantitative base for decision making. And the basic components are logic and common sense. Techniques are statistical inference, mathematical programming etc. The 7 step methodology model was explained: They are 1. Identify the problem. 2. Understand the system 3. Formulate a mathematical model 4. Verify the model 5. Select the best alternative 6. Present - -- analysis 7. Implement and evaluate. Examples: HP, Taco Bell, At&T etc. What is a model? A model is an invention of the mind, with a limited degree of reality which constitute a formal approach to decision making. 5 sub models that compromise a complete model and they are Physical/analog, mathematical, statistical, conceptual, visualization. Major benefits of models is a five step process and they are: 1. Statement of the purpose of the model, 2. Formulation of the theory or model 3. Initial verification by comparison with available observations 4. Use of the model to predict future behaviour 5. Refinement of the model. VALUE ADDITION SUMMARY OF THE CASEAlthough China produces 1.1 billion tons of coal per year, demand is projected at almost 1.6 billion tons in 2000. Transport bottlenecks, coal and electricity shortages, and worsening air pollution threaten the country's double-digit GNP growth. To address these problems, the World Bank and the Chinese State Planning Commission developed a decision support system consisting of a mixed-integer program, a geographic information system, and related sub models. The Coal Transport Study (CTS) model covers coal mining, washing, and transport; thermal, hydro, and nuclear power generation; electricity transmission; pollution levels; and scrubbers; which together will require at least $240 billion in new investments over a 15-year horizon. The analysis results influenced several government policies concerning GNP growth, coal imports, and various capital investments, with a potential benefit of about $6.4 billion from 1991 to 2005.

China produces 1.1 billion tons of coal every year. However, in 1995 demand was estimated to be about 1.6 billion tons. In addition, China faced air pollution that could threaten its national product growth rate (GNP). These problems were identified by the Chinese State Planning Commission and the World Bank as important to the continued growth of Chinas GNP. Defining the Problem

To analyse some of the problems associated with the delivery of coal and electricity, the Chinese State Planning Commission developed a comprehensive model called the Coal Transport Study (CTS) model. The model specified key components in the generation, transmission, and demand for electricity. Developing a model

In addition to historical data, the model required forecasts of future demand and the potential environmental impact of various energy slurs and uses, In addition, specific data concerning the various stages of coal and electricity production were needed.Acquiring Input Data

Instead of developing and reporting one solution, the decision modelling team analysed 16 different solutions or possibilities. These solutions revealed that the investment in new coal electricity systems could be as high as $250 billion over 10 year period. The new system would have to deliver 2 billion tonnes of coal.Developing a Solution

Assumptions of the model and the solutions were carefully tested. About half a year was spent in testing the data, the model and the solutions. This included running a series of tests on the model and the data, using known data to make sure that the data and the model produced results consistent with the correct situation. This testing resulted in fine tuning the data to make them more accurate. After testing, corrections and adjustments were made to make sure that the results were as accurate as possible.Testing the solution

The solutions also resulted in major findings. First, the government should plan on an 8%-9% growth in power needs. Second, railways would continue to be the dominant transportation system for coal. Next, coal distribution could be greatly increased by increasing the volume and length of coastal and inland waterways. The chance of building and slurry pipelines was slim. In addition, there were number of specific findings on how coal should be handled and processed into energy to reduce pollution and negative environmental consequences.Analysing the results and Sensitivity Analysis

Implementation of the CTS model resulted in a new steam coal-washing procedure, the construction of improved railway system and a new port, and the use of coal imports. In addition, the planning commission developed a sophisticated model for strategic level investment planning. The model was expected to be extended to form energy planning of the year 2010. Implementing the results

CONCLUSIONIt is very important to realise that before an actual implementation, one should cycle through the first four steps a number of times so as to ensure that a reasonably valid model has been achieved. The benefits are as follows: 1. Time efficient thereby increasing accuracy. 2. Reduces the chances of errors, assumptions, and poor judgements. 3. Promotes high quality decisions and reduces risks. Thereby, decision modelling addresses the complex issues by breaking down into simple steps which enables the decision maker to arrive at the optimal decision.

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