Inventory Policy
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TABLE OF CONTENTS
1. Introduction to simulation theory
1.1 What is simulation?
1.1.2 Why Simulate?
1.1.3 Typical Applications
1.2 Definition of Systems and Models
1.2.1 Types of Systems
1.3 Monte Carlo Simulation
2. Simulation of Inventory Policies
2.1 Probability Distribution Table
2.2 Inventory Policy 1
2.2.1 Simulation Table
2.2.2 Calculation costs
2.2.3 Analysis
2.3 Inventory Policy 2
2.3.1 Simulation Table
2.3.2 Calculation costs
2.3.3 Analysis
2.4 Inventory Policy 3
2.4.1 Simulation Table
2.4.2 Calculation costs
2.4.3 Analysis
2.5 Inventory Policy 4
2.5.1 Simulation Table
2.5.2 Calculation costs
2.5.3 Analysis
2.6 Inventory Policy 5
2.6.1 Simulation Table
2.6.2 Calculation costs
2.6.3 Analysis
2.7 Inventory Policy 6
2.7.1 Simulation Table
2.7.2 Calculation costs
2.7.3 Analysis
2.8 Inventory Policy 7
2.8.1 Simulation Table
2.8.2 Calculation costs
2.8.3 Analysis
2.9 Inventory Policy 8
2.9.1 Simulation Table
2.9.2 Calculation costs
2.9.3 Analysis
3. Recommendations
4. Conclusion
5. Bibliography
1. Basic Simulation Theory
1.1 What is simulation?
Simulation is a representation of reality through the use of a model or other device which will react in the same manner as reality under a given set of conditions. In order for simulation to happen, a model must be developed. This model combines the key characteristics or functions of the experimental approach and the specific conditions of the use of computer. The model represents the system itself, whereas the simulation represents the operation of the system over time. The operation can be simple such as using a machine or a whole factory with all its complexity. Therefore, simulation can be used to show the ultimate real effects of alternative conditions and courses of actions. It is also used to study the characteristics and predict performance of a real system.
1.1.2 Why Simulate?
We have found that the more complex a process is, the greater the need is to employ computer-based
TABLE OF CONTENTS
1. Introduction to simulation theory
1.1 What is simulation?
1.1.2 Why Simulate?
1.1.3 Typical Applications
1.2 Definition of Systems and Models
1.2.1 Types of Systems
1.3 Monte Carlo Simulation
2. Simulation of Inventory Policies
2.1 Probability Distribution Table
2.2 Inventory Policy 1
2.2.1 Simulation Table
2.2.2 Calculation costs
2.2.3 Analysis
2.3 Inventory Policy 2
2.3.1 Simulation Table
2.3.2 Calculation costs
2.3.3 Analysis
2.4 Inventory Policy 3
2.4.1 Simulation Table
2.4.2 Calculation costs
2.4.3 Analysis
2.5 Inventory Policy 4
2.5.1 Simulation Table
2.5.2 Calculation costs
2.5.3 Analysis
2.6 Inventory Policy 5
2.6.1 Simulation Table
2.6.2 Calculation costs
2.6.3 Analysis
2.7 Inventory Policy 6
2.7.1 Simulation Table
2.7.2 Calculation costs
2.7.3 Analysis
2.8 Inventory Policy 7
2.8.1 Simulation Table
2.8.2 Calculation costs
2.8.3 Analysis
2.9 Inventory Policy 8
2.9.1 Simulation Table
2.9.2 Calculation costs
2.9.3 Analysis
3. Recommendations
4. Conclusion
5. Bibliography
1. Basic Simulation Theory
1.1 What is simulation?
Simulation is a representation of reality through the use of a model or other device which will react in the same manner as reality under a given set of conditions. In order for simulation to happen, a model must be developed. This model combines the key characteristics or functions of the experimental approach and the specific conditions of the use of computer. The model represents the system itself, whereas the simulation represents the operation of the system over time. The operation can be simple such as using a machine or a whole factory with all its complexity. Therefore, simulation can be used to show the ultimate real effects of alternative conditions and courses of actions. It is also used to study the characteristics and predict performance of a real system.
1.1.2 Why Simulate?
We have found that the more complex a process is, the greater the need is to employ computer-based