Week
|
Topic
|
Readings
|
| 1 |
Dynamic Programming. Deterministic models,
Discrete state and continuous state models |
11.1-11.3 |
| 2 |
Probabilistic models, Applications |
11.4 |
| 3 |
Markov Chains. Stochastic processes, Markov
chains, Chapman-Colmogorov equations |
16.1-16.3 |
| 4 |
Classification of states of a Markov Chain, First
passage times |
16.4,16.6 |
| 5 |
Long-run properties of Markov Chains, Long-run
expected cost, Absorbing chains |
16.5,16.7 |
| 6 |
Mid-term Exam |
|
| 6 |
Queueing Theory. Basic structure of queueing
systems, Examples of real queueing systems, Role of the exponential distribution,
Birth-and-Death Process, Special cases: Pure Birth process, Pure Death
Process |
17.1-17.5 |
| 7 |
Queueing models based on the Birth-and-Death
Process, M/M/s, M/M/s/K, M/M/s/N/N, Special cases: Self-service model,
Erlang model |
17.6 |
| 8 |
Queueing models involving Nonexponential Distributions,
Priority-Discipline queueing models, Queueing networks |
17.7-17.9 |
| 9 |
Inventory Theory. Examples, Components
of Inventory models, Deterministic continuous review models |
19.1-19.3 |
| 10 |
Deterministic periodic review models, Production
planning model, Integer programming formulation, Probabilistic continuous
review models: Service-level model, Stochastic EOQ model with fixed lead
time |
19.4-19.5 |
| 11 |
Final Exam |
|