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) |
To know modern logistics activities and to learn basic legislation on these issues |
|
2) |
Can use and know the concepts and current theories in the field of international logistics and supply chain management (logistics system design and planning, purchasing, production, stock management, warehouse and transportation management, sales and distribution, strategic partnerships, risk management, performance measurement etc.) |
|
3) |
Using appropriate theory, tools and methods, we can develop effective logistics and supply chain strategies, design logistic systems to support the mission and objectives of the business, and make decisions. |
|
4) |
To know the rules of opening up to international markets with the knowledge of new marketing and sales techniques and to be able to apply them |
|
5) |
Understands the complex and rapidly changing global and national business world and the main actors, conditions and dynamics in the international logistics environment. |
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6) |
Understands problems in supply chain management and applications can produce innovative solutions and can be found in recommendations for improving performance. |
|
7) |
Can use widely used software and applications in the field of logistics management. |
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8) |
To stay in the relevant networks to keep up to date on personal and professional competence, to follow the changes in the sector in which they work and to improve themselves constantly. |
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