Week |
Subject |
Related Preparation |
1) |
• Discuss the differences between quantitative and qualitative analysis.
• Describe the problem.
• Analyzes model development. |
|
2) |
• Explain the advantages of the mathematical model.
• Explain mathematical models grouped by race.
• Describe the problem.
• Develops models.
• Obtain data entries.
• Develops solutions.
• Tests the solution.
• Analyzes the results. |
|
3) |
• Explain the basic concepts of probability.
• Lists the types of probability.
• Discuss the difference between statistically dependent and independent events.
• Analyzes the probability distribution of the intermittent random variable.
• Analyzes the probability distribution of continuous random variables. |
|
4) |
• Solve questions with the Binomial formula.
• Solve questions with Binomial tables.
• Calculates the area under the normal curve.
• Explains how to use the standard normal distribution chart. |
|
5) |
• Describe decision theorem.
• Define decision-making under uncertainty based on optimism criteria.
• Define decision-making under pessimism criteria under uncertainty.
• Define decision-making under the criterion of reality (Hurwicz Criterion) under uncertainty.
• Define decision making under unequal probability (laplace).
• Define decision making under the minimax criterion under uncertainty. |
|
6) |
• Describes and explains sensitivity analysis.
• Bayesian analysis shows how the probability values are predicted.
• Calculates revised probabilities.
• Discuss possible problems in the survey results.
• Demonstrate measuring and forming the benefit curve. |
|
7) |
• Classify regression models.
• Explain how to interpret the scatter diagrams.
• Measures the suitability of the regression model.
• Explain the assumption of the regression model.
• Tests the meaning of the model.
• Evaluates multiple regression models. |
|
8) |
• mid-term exam.
• Explain the advantages of the mathematical model.
• Explain mathematical models grouped by race.
• Analyzes the probability distribution of the intermittent random variable.
• Calculates the area under the normal curve.
• Explains how to use the standard normal distribution chart.
• Define decision-making under the criterion of reality (Hurwicz Criterion) under uncertainty.
• Define decision making under unequal probability (laplace).
• Bayesian analysis shows how the probability values are predicted.
• Explain the assumption of the regression model.
• Tests the meaning of the model. |
|
9) |
• Defines time series models.
• Defines causality models.
• Describe qualitative models.
• Explain how scatter diagrams can be used to interpret time series.
• Analyzes trend projections.
• Analyzes seasonal changes.
• Analyzes seasonal changes with trends. |
|
10) |
• Graphical representation of how constraints are used.
• Isoprofit analyzes the line solution.
• Analyze the corner point dissolution method.
• Explain idle and residual concepts. |
|
11) |
• Analyzes the 'non-solvable' special case in linear programming.
• In linear programming, 'infinity' analyzes the special case.
• Analyzes the 'now' special case in linear programming.
• In linear programming, the 'alternative optimal solution' analyzes the special case.
• The minimization solves the problem.
• Analyzes four special cases in linear programming.
• Describes and explains sensitivity analysis. |
|
12) |
• Identify and explain marketing practices.
• Identify and explain production practices.
• Identify and explain business planning practices.
• Identify and disclose their financial applications.
• Identifies and explains the component mixing applications.
• Identify and explain transportation practices. |
|
13) |
• Decodes the model with Binary (0-1) values.
• Identify and explain nonlinear objective function and linear constraints.
• Identify and explain nonlinear objective function and nonlinear constraints.
• Identify and explain linear objective function and nonlinear constraints. |
|
14) |
• Identifies and explains the terminology of the game concept.
• Identify and explain the Minimax criteria.
• Identify and explain pure strategy games.
• Identify and explain mixed strategy games.
• Identify and explain dominant strategy games. |
|
15) |
Final Exam |
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|
Program Outcomes |
Level of Contribution |
1) |
Can understand and use the basic knowledge and existing theories about logistics and supply chain management (logistics systems design and planning, purchasing, manufacturing, inventory management, strategic alliances, risk management, performance measurement etc.) |
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2) |
Can develop appropriate strategies for efficient usage of logistics and supply chain system, and can make system designs which supports the enterprice’s mission an vision |
|
3) |
Can identify uncertainties in logistics and supply chain processes, and take measures for managing risks |
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4) |
Can evaluate situations in supply chain management and determine what problems in the system and analyze them |
|
5) |
Can generate innovative solutions to problems of supply chain management and applications and can make recommendations for improving performance |
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6) |
Do know general concept and practice of the basic administration science such as economics, accounting, human resource management, international trade and integrate this knowledge for designing logistics and supply chain systems. |
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7) |
Can understand complex and rapidly changing global and national business community and the main players, conditions and dynamics of international logistics environment |
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8) |
It aware of the legal frameworks that shape the international logistics activities and evaluates appropriateness of these activities to the national and international legislation and regulations |
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9) |
Selects and the necessary resources to collect and analyze data in matters relating to the area and uses effectively and makes correct inferences from researches and be able to report these data |
|
10) |
Can use softwares and applications are using in the field of logistics management |
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