SCHEDULING

AIM

The students who succeeded the course will be able to identify, formulate and solve various problems in the area of scheduling (deterministic and stochastic).

CONTENT

This course contains; Introduction ,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 intermadiate storage),Felexible Flow Shops,Open Shop Scheduling,Jop Shop Scheduling,General Purpose Procedures for Deterministic Schedule,Stochastic Moldels: Preliminaries,Stochastic Models.

1. 1

   Students will be able to model deterministic single machine problems

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

2. 2

   Students will be able to model deterministic parallel machine problems

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

3. 3

   Students will be able to model open shop scheduling problems

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

4. 4

   Students will be able to model job shop scheduling problems

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

WEEKLY PLAN

1. WEEK 1

   Introduction

2. WEEK 2

   Deterministic Models: Preliminaries: Framework and Notation

3. WEEK 3

   Deterministic Models: Preliminaries: Classes of Schedules and Complexity Hierarchy

4. WEEK 4

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

5. WEEK 5

   Deterministic Single Machine Models (Total weighted tardiness, makespan)

6. WEEK 6

   Deterministic Parallel Machine Models-1

7. WEEK 7

   Deterministic Parallel Machine Models-2

8. WEEK 8

   Deterministic Flowshops (with limited/unlimited intermadiate storage)

9. WEEK 8

   Felexible Flow Shops

10. WEEK 10

    Open Shop Scheduling

11. WEEK 11

    Jop Shop Scheduling

12. WEEK 12

    General Purpose Procedures for Deterministic Schedule

13. WEEK 13

    Stochastic Moldels: Preliminaries

14. WEEK 14

    Stochastic Models

ASSESSMENT

• Rate of Midterm Exam to Success30%
• Rate of Final Exam to Success70%

WORKLOAD

READING

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

TEACHING STAFF

• Assoc.Prof. Yasin GÖÇGÜNCOORDINATOR