The Metaheuristics Stream at OR64 Annual Conference will focus on theory and practice-oriented studies on:
* Design of metaheuristics and nature-inspired algorithms including evolutionary and population-based search methods and their implementation in real-life applications
* Hybrid metaheuristics and the intersection of metaheuristics and other related areas including parallel computing, quantum computing, data science and machine learning
* Systems to build systems, hyper-heuristics, adaptive/self-adaptive/multi-level metaheuristics
* Extensible and white-box metaheuristics
* Developing the theoretical/analytical foundations of (meta/hyper-)heuristics
This stream welcomes all working or interested in developing knowledge and excitement about the general field of metaheuristics. It will improve your understanding of the latest advancements in the field, deepen your appreciation of metaheuristics as a problem-solving method, and it will guide you in your search for an opportunity to contribute to the literature of metaheuristics in the future.
Key dates:
* 30 June 2022: Abstract submission deadline
* 30 June 2022: Early bird registration deadline
* 8 July 2022: Notification of acceptance sent regarding abstracts
* 13-15 September 2022: conference held at the University of Warwick, UK
Please submit your abstracts and register for the conference using the following link:
https://theorsociety.eventsair.com/or64-annual-conference/
For further inquiries about the metaheuristics stream, contact the organisers: Ali Hassanzadeh<https://www.linkedin.com/in/ali-hassanzadeh/> (University of Manchester, ali.h@manchester.ac.uk) and Arijit De<https://www.linkedin.com/in/arijit-de-611a5815/> (University of Manchester, arijit.de@Manchester.ac.uk).
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Ali Hassanzadeh, PhD | Assistant Professor in Management Science
Alliance Manchester Business School<https://www.alliancembs.manchester.ac.uk/research/management-sciences-and-marketing/>, The University of Manchester<https://www.manchester.ac.uk/>
ali.h [AT] manchester.ac.uk | Website<https://www.research.manchester.ac.uk/portal/ali.h.html>
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