SCHEDULING THEORY

AIM

Defines and solves various problems related to scheduling.

CONTENT

This course contains; Introduction to Scheduling,Deterministic Models: Preliminaries: Framework and Notation,Deterministic Models: Preliminaries: Classes of Schedules and Complexity Hierarchy,Deterministic Single Machine Models (Total weighted completion time, maximum lateness, number of tardy jobs),Deterministic Single Machine Models (Total weighted tardiness, makespan),Deterministic Parallel Machine Models-1,Deterministic Parallel Machine Models-2,Deterministic Flowshops (with limited/unlimited intermediate storage),Flexible Flow Shops,Open Shop Scheduling,Job Shop Scheduling,General Purpose Procedures for Deterministic Schedule,Stochastic Models: Preliminaries,Stochastic Models.

1. 1

   Models open shop scheduling problems.

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

2. 2

   Models deterministic single-machine problems.

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

3. 3

   Models deterministic parallel machine problems.

   Taught by: Discussion Method, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

4. 4

   Models job shop scheduling problems.

   Taught by: Discussion Method, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

WEEKLY PLAN

1. WEEK 1

   Introduction to Scheduling

   Preparation: Lecture Notes

2. WEEK 2

   Deterministic Models: Preliminaries: Framework and Notation

   Preparation: Lecture Notes

3. WEEK 3

   Deterministic Models: Preliminaries: Classes of Schedules and Complexity Hierarchy

   Preparation: Lecture Notes

4. WEEK 4

   Deterministic Single Machine Models (Total weighted completion time, maximum lateness, number of tardy jobs)

   Preparation: Lecture Notes

5. WEEK 5

   Deterministic Single Machine Models (Total weighted tardiness, makespan)

   Preparation: Lecture Notes

6. WEEK 6

   Deterministic Parallel Machine Models-1

   Preparation: Lecture Notes

7. WEEK 7

   Deterministic Parallel Machine Models-2

   Preparation: Lecture Notes

8. WEEK 8

   Deterministic Flowshops (with limited/unlimited intermediate storage)

   Preparation: Lecture Notes

9. WEEK 9

   Flexible Flow Shops

   Preparation: Lecture Notes

10. WEEK 10

    Open Shop Scheduling

    Preparation: Lecture Notes

11. WEEK 11

    Job Shop Scheduling

    Preparation: Lecture Notes

12. WEEK 12

    General Purpose Procedures for Deterministic Schedule

    Preparation: Lecture Notes

13. WEEK 13

    Stochastic Models: Preliminaries

    Preparation: Lecture Notes

14. WEEK 14

    Stochastic Models

    Preparation: Lecture Notes

ASSESSMENT

• Rate of Midterm Exam to Success50%
• Rate of Final Exam to Success50%

WORKLOAD

READING

• Michael Pinedo, Scheduling: Theory, Algorithms, and Systems, 4th Edition, Springer.

TEACHING STAFF

• Prof.Dr. Hakan TOZANCOORDINATOR
• Prof.Dr. Hakan TOZAN