posted by user: sadegh_rk || 2793 views || tracked by 3 users: [display]

PATAT 2022 : Practice and Theory of Automated Timetabling

FacebookTwitterLinkedInGoogle


Conference Series : Practice and Theory of Automated Timetabling
 
Link: http://www.patatconference.org/patat2022/#home
 
When Aug 30, 2022 - Aug 2, 2022
Where Leuven, Belgium
Submission Deadline Mar 23, 2022
Notification Due May 6, 2022
Final Version Due May 13, 2022
Categories    transportation   machine learning   healthcare
 

Call For Papers

Call for Papers

The biennial conference on Practice and Theory of Automated Timetabling (PATAT) has been a forum for over 20 years welcoming both researchers and practitioners of timetabling to exchange ideas. PATAT 2022 will be the thirteenth edition in this international series.
Aim and Scope

Whether it is sporting events, educational institutions, transportation or employee management the construction of efficient timetables which provide the maximum in way of flexibility for all constituent parts is as important as it is challenging. An increasingly important aspect within organisations is an automated approach which optimises all aspects of resource usage. In doing so a number of quantitative and qualitative challenges must be dealt with from both a technical and practical perspective.

An important aim of the conference is to align the needs of practitioners and the objectives of researchers. This is achieved through the presentation and application of leading edge research techniques. Practitioners and Researchers alike are encouraged to present their work and experiences with the overall goal of developing efficient and practical solutions. With this goal in mind, at PATAT 2022, researchers and practitioners will be brought together through a number of key presentations and workshops.

Topics of interest and themes of the conference include, but not limited to:

Algorithm Portfolios
Employee Rostering
Fuzzy Systems
Hybrid Methods
Machine Learning
Multi-criteria Decision Making
Resource Capacity Planning
Timetabling in Transport
Constraint-Based Methods
AI-based Systems
Graph Colouring
Hyper-heuristics
Mathematical Programming
Multi-objective Approaches
Sports Timetabling
Tools and Applications
Educational Timetabling
Foundational Studies
Heuristic Search
Knowledge Based Systems
Metaheuristics
Parallel/Distributed Computing
Timetabling in Healthcare

Publication

Authors are invited to submit their work in one of three categories:

Full papers: Authors should submit papers describing significant, original and unpublished work.
Abstracts: People who wish to give a talk (e.g. practitioners, researchers with preliminary or incomplete papers) but do not want to submit a full paper can submit abstracts of up to 1000 words.
System demonstrations: Authors can also submit an abstract, describing the major properties and contribution of implemented and/or commercial timetabling systems.

All submissions will be peer reviewed by at least three members of the programme committee. Accepted papers will be invited for an oral presentation at the event and included in the PATAT 2018 proceedings after they are presented.

Related Resources

IDEAL 2024   Intelligent Data Engineering and Automated Learning
CLNLP 2025   2025 2nd International Conference on Computational Linguistics and Natural Language Processing
IEEE Big Data - MMAI 2024   IEEE Big Data 2024 Workshop on Multimodal AI
VISAPP 2025   20th International Conference on Computer Vision Theory and Applications
SPIE-Ei/Scopus-DMNLP 2025   2025 2nd International Conference on Data Mining and Natural Language Processing (DMNLP 2025)-EI Compendex&Scopus
JSS SI: AI testing and analysis 2024   [JSS - Elsevier] Special Issue on Automated Testing and Analysis for Dependable AI-enabled Software and Systems
Ei/Scopus-ACAI 2024   2024 7th International Conference on Algorithms, Computing and Artificial Intelligence(ACAI 2024)
ICAPS 2025   International Conference on Automated Planning and Scheduling
AMLDS 2025   IEEE--2025 International Conference on Advanced Machine Learning and Data Science