IA267 Scheduling

Faculty of Informatics
Spring 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
there are 30 fields of study the course is directly associated with, display
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