EMO 2027
Welcome to the 14th International Conference on Evolutionary Multi-Criterion Optimization, hosted by the University of Exeter in the beautiful city of Exeter, United Kingdom.
About EMO 2027
The International Conference on Evolutionary Multi-Criterion Optimization (EMO) is the premier venue for researchers and practitioners working on multi-objective and many-objective optimization using evolutionary and nature-inspired computation approaches.
EMO 2027 will bring together leading experts from academia and industry to present and discuss the latest advances in evolutionary multi-objective optimization, including theoretical foundations, algorithm design, performance assessment, and real-world applications.
Conference Format
EMO 2027 will feature:
- 1 Tutorial Day: Monday, 5 April - In-depth tutorials on cutting-edge topics
- 3 Scientific Days: Tuesday-Thursday, 6-8 April - Keynotes and single-track sessions across EMO, MCDM, and Industry topics
- Social Events: Welcome reception, boat tour, and conference banquet
- Best Paper Awards: Recognition of outstanding contributions
Papers
Peer-reviewed research presentations from the EMO community
Keynotes
Inspiring talks from world-leading researchers
Tutorials
Hands-on learning from leading experts
Networking
Connect with peers at social events
Important Dates
All dates are tentative and subject to change
Paper Submission Deadline
TBCSubmit full papers via the conference submission system
Author Notification
TBCAuthors will be notified of acceptance decisions
Camera-Ready Deadline
TBCFinal versions of accepted papers due
Early Registration Deadline
TBCRegister early for discounted rates
Regular Registration Deadline
TBCFinal deadline for standard registration rates
Conference Begins
April 05, 2027Tutorial day and welcome reception
Venue
EMO 2027 will be held at the XFi Building on the University of Exeter’s picturesque Streatham Campus. The venue features modern conference facilities including the 174-seat Henderson Lecture Theatre and the XFi break-out area for posters and networking.
Topics of Interest
EMO 2027 welcomes submissions on all aspects of evolutionary multi-objective optimization, including but not limited to:
- Multi-objective and many-objective optimization
- Theoretical foundations of EMO algorithms
- Algorithm design and performance assessment
- Preference-based and interactive methods
- Real-world applications
- Benchmarking and test problems
- Hybrid and memetic approaches
- Machine learning and EMO
- Dynamic and robust optimization
- Large-scale optimization
Sponsors & Partners
Interested in sponsoring EMO 2027? Contact us for sponsorship opportunities.
Become a Sponsor