PA167 Scheduling

Faculty of Informatics
Spring 2019
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. Mgr. Hana Rudová, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Eva Hladká, Ph.D.
Department of Computer Systems and Communications – Faculty of Informatics
Supplier department: Department of Computer Systems and Communications – Faculty of Informatics
Timetable
Thu 21. 2. to Thu 16. 5. Thu 12:00–13:50 A320
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
Course provides information about various types of scheduling problems from theoretical and especially practical perspective, it demonstrates general solution approaches for scheduling problems and the most important approaches for specific practical scheduling problems.
Learning outcomes
Graduate will be able to identify and describe various scheduling problems appearing in practice.
Graduate will be aware of general methods applicable to solve scheduling problems from in manufacturing and services.
Graduate will be aware of algorithms and solution methods for scheduling problems such as project planning, scheduling of flexible assembly systems, or educational timetabling.
Graduate will be able to solve scheduling problems with the help of studied algorithms and approaches.
Syllabus
  • Examples, scheduling problem, Graham classification.
  • General purpose scheduling procedures: dispatching rules, mathematical programming, local search, constraint programming.
  • Project planning and scheduling: project representation, critical path, time/cost trade-offs, workforce constraints.
  • Machine scheduling: dispatching rules, branch&bound, mathematical programming, shifting bottleneck.
  • Scheduling of flexible assembly systems: paced and unpaced systems, flexible flow shop.
  • Reservations: interval scheduling, reservation with slack.
  • Timetabling: workforce constraints, tooling constraints, relation to interval scheduling. Educational timetabling, university course timetabling.
  • Workforce scheduling.
Literature
  • PINEDO, Michael. Planning and Scheduling in Manufacturing and Services. Springer, 2005. Springer Series in Operations Research. info
Teaching methods
The course is taught in the form of standard lecture. Lectures are oriented on presentation of various solving methods for different types of scheduling problems. Lectures include exercises to practice studied methods. Comprehensive list of exercises related to the subject covers all studied areas and allows self-study.
Assessment methods
There is following expected evaluation given as a sum of points for homeworks and final written exam: A 90 and more, B 80-89, C 70-79, D 60-69, E 50-59.
There are two homeworks during a semester. It is possible to get points up to 10 points per homework. Each student is required to obtain 8 points at least from the total point of 20 points.
Each student can get 1 bonus point for activity in each lecture (e.g., student response to several easy questions and/or student questions to clarify some part of the lecture; student response to one harder question). Bonus points will be given starting from the second lecture, i.e., it is possible to get up to 11 bonus points for activity at eleven lectures.
Final written exam consists of about 7 examples and it is possible to get up to 80 points. Exam includes questions: examples (the problem is given, the choice of method might be given, typical solution: computation of the schedule), comparisons of methods or definitions, algorithms, definitions. A list of about 240 questions is available as a source for written exams.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://www.fi.muni.cz/~hanka/rozvrhovani
The course is also listed under the following terms Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2017, Spring 2018, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.
  • Enrolment Statistics (Spring 2019, recent)
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