FI:IA267 Scheduling - Course Information
IA267 Scheduling
Faculty of InformaticsSpring 2025
- Extent and Intensity
- 2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
In-person direct teaching - Teacher(s)
- doc. Mgr. Hana Rudová, Ph.D. (lecturer)
- Guaranteed by
- doc. Mgr. Hana Rudová, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - 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
- Image Processing and Analysis (programme FI, N-VIZ)
- Bioinformatics and systems biology (programme FI, N-UIZD)
- Computer Games Development (programme FI, N-VIZ_A)
- Computer Graphics and Visualisation (programme FI, N-VIZ_A)
- Computer Networks and Communications (programme FI, N-PSKB_A)
- Cybersecurity Management (programme FI, N-RSSS_A)
- Discrete algorithms and models (programme FI, N-TEI)
- Formal analysis of computer systems (programme FI, N-TEI)
- Graphic design (programme FI, N-VIZ)
- Graphic Design (programme FI, N-VIZ_A)
- Hardware Systems (programme FI, N-PSKB_A)
- Hardware systems (programme FI, N-PSKB)
- Image Processing and Analysis (programme FI, N-VIZ_A)
- Information security (programme FI, N-PSKB)
- Information Security (programme FI, N-PSKB_A)
- Quantum and Other Nonclassical Computational Models (programme FI, N-TEI)
- Computer graphics and visualisation (programme FI, N-VIZ)
- Computer Networks and Communications (programme FI, N-PSKB)
- Principles of programming languages (programme FI, N-TEI)
- Cybersecurity management (programme FI, N-RSSS)
- Services development management (programme FI, N-RSSS)
- Software Systems Development Management (programme FI, N-RSSS)
- Services Development Management (programme FI, N-RSSS_A)
- Software Systems Development Management (programme FI, N-RSSS_A)
- Software Systems (programme FI, N-PSKB_A)
- Software systems (programme FI, N-PSKB)
- Machine learning and artificial intelligence (programme FI, N-UIZD)
- Computer Games Development (programme FI, N-VIZ)
- Processing and analysis of large-scale data (programme FI, N-UIZD)
- Natural language processing (programme FI, N-UIZD)
- Course objectives
- The course provides information about various types of scheduling problems from theoretical and practical perspective. It demonstrates general solution approaches for scheduling problems and the most important approaches for various classes of scheduling problems from practice.
- Learning outcomes
- The graduate will be able to identify and describe various scheduling problems appearing in practice.
The graduate will be knowledgeable of scheduling problems in manufacturing, real-time systems, and services.
The graduate will be aware of algorithms and solution methods for project planning, scheduling in real-time systems, scheduling of flexible assembly systems, or educational timetabling.
The graduate will be able to solve scheduling problems with the help of studied algorithms and approaches. - Syllabus
- Introduction: examples, scheduling problem, Graham classification.
- Machine scheduling: dispatching rules, branch&bound, mathematical programming.
- Project planning: project representation, critical path, time/cost trade-offs, workforce constraints.
- Shop scheduling: job-shop problem, disjunctive graph representation, branch&bound, shifting bottleneck, flexible assembly systems.
- Real-time systems: introduction, reference model, off-line scheduling, static priority scheduling, dynamic priority scheduling, real-time operating systems.
- Reservations and timetabling: interval scheduling, reservation with slack, workforce and tooling constraints, educational timetabling.
- 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 a standard lecture. Lectures are oriented on the presentation of various methods for different types of scheduling problems. Lectures include exercises to practice studied methods.
- Assessment methods
- The following expected evaluation is given as a sum of points for two written tests and bonus points: A 90 and more, B 80-89, C 70-79, D 60-69, E 55-59.
There is one written test during a semester for 25 points. Each student is required to obtain 11 points at least from the intra-semester test.
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).
The final written exam consists of about 7 examples. It is necessary to get more than 40 out of 75 points. The 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, and definitions. - Language of instruction
- English
- Further Comments
- The course is taught annually.
The course is taught: every week. - Teacher's information
- https://is.muni.cz/el/fi/jaro2024/PA167/index.qwarp
- Permalink: https://is.muni.cz/course/fi/spring2025/IA267