1. |
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Newsvendor Problem 1 |
Design, analyze, and manage a manufacturing
or service system with uncertainty.
Solve a single period decision problem containing uncertainty or randomness. |
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2. |
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Newsvendor Problem 2 |
Design, analyze, and manage a manufacturing
or service system with uncertainty.
Solve a single period decision problem containing uncertainty or randomness. |
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3. |
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Newsvendor Problem 3 |
Design, analyze, and manage a manufacturing
or service system with uncertainty.
Solve a single period decision problem containing uncertainty or randomness. |
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4. |
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Discrete Time Markov Chain 1 |
How to manage uncertainty when you are selling
perishable items. How should we Model di erently if we are running a business dealing with durable or non-perishable goods? |
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Discrete Time Markov Chain 1 |
How to manage uncertainty when you are selling
perishable items. How should we Model di erently if we are running a business dealing with durable or non-perishable goods? |
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Discrete Time Markov Chain 1 |
How to manage uncertainty when you are selling
perishable items. How should we Model di erently if we are running a business dealing with durable or non-perishable goods? |
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5. |
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Discrete Time Markov Chain 2 |
How to manage uncertainty when you are selling
perishable items. How should we Model di erently if we are running a business dealing with durable or non-perishable goods? |
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Discrete Time Markov Chain 2 |
How to manage uncertainty when you are selling
perishable items. How should we Model di erently if we are running a business dealing with durable or non-perishable goods? |
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6. |
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Discrete Time Markov Chain 2 |
How to manage uncertainty when you are selling
perishable items. How should we Model di erently if we are running a business dealing with durable or non-perishable goods? |
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Discrete Time Markov Chain 2 |
How to manage uncertainty when you are selling
perishable items. How should we Model di erently if we are running a business dealing with durable or non-perishable goods? |
|
|
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Discrete Time Markov Chain 2 |
How to manage uncertainty when you are selling
perishable items. How should we Model di erently if we are running a business dealing with durable or non-perishable goods? |
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7. |
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Discrete Time Markov Chain 3 |
How to manage uncertainty when you are selling
perishable items. How should we Model di erently if we are running a business dealing with durable or non-perishable goods? |
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8. |
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Poisson Process 1 |
The way we modeled was to denote the inter-arrival times between customers by a random variable and assumed that the random
variable has a exponential distribution. |
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Poisson Process 1 |
The way we modeled was to denote the inter-arrival times between customers by a random variable and assumed that the random
variable has a exponential distribution. |
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9. |
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Poisson Process 2 |
a special case: the case where the inter-arrival times follow iid exponential distribution. We will learn how it is different from other distributions. |
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Poisson Process 2 |
a special case: the case where the inter-arrival times follow iid exponential distribution. We will learn how it is different from other distributions. |
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10. |
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Continuous Time Markov Chain 1 |
The time period is discretized so that time is denoted by integers. Consider discrete‐time stochastic process having discrete state space |
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Continuous Time Markov Chain 1 |
The time period is discretized so that time is denoted by integers. Consider discrete‐time stochastic process having discrete state space |
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Continuous Time Markov Chain 1 |
The time period is discretized so that time is denoted by integers. Consider discrete‐time stochastic process having discrete state space |
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Continuous Time Markov Chain 1 |
The time period is discretized so that time is denoted by integers. Consider discrete‐time stochastic process having discrete state space |
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11. |
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Continuous Time Markov Chain 2 |
A stochastic process is a continuous time Markov chain with state space |
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Continuous Time Markov Chain 2 |
A stochastic process is a continuous time Markov chain with state space |
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12. |
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Queueing basics 1 |
Queueing theory deals with a set of systems having waiting space. Analyzing a simple queue, a set of queues connected with each other will be covered as well in the end. |
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13. |
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Queueing basics 2 |
Design the system. How can we determine the number of server and customer, size of waiting capacity? |
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Queueing basics 2 |
Design the system. How can we determine the number of server and customer, size of waiting capacity? |
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Queueing basics 2 |
Design the system. How can we determine the number of server and customer, size of waiting capacity? |
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14. |
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Queueing basics 3 |
How does the system perform? For example that Utilization of servers, Average waiting time in queue, Average staying time in the system |
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15. |
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Queueing basics 4 |
Case study |
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Queueing basics 4 |
Case study |
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