A new blog post outlining our very latest results on a continuous learning system NELLI* that adapts to changing problem characteristics
A new paper on the life-long learning capabilities of NELLI* accepted for publication at PPSN 2014
The ROLL team will be presenting three papers at GECCO 2014 in Vancouver
- AIS Track: An Improved Immune Inspired Hyper-Heuristic for Combinatorial Optimisation Problems
- PURO Workshop: A Real-World Employee Scheduling and Routing Application
- Hot Off the Press Track . A Lifelong Learning Hyper-Heuristic for Bin-Packing Evolutionary Computation, MIT Press
A pre-print of our new paper on Lifelong Learning with HyperHeuristics accepted for publication by Evolutionary Computation (MIT Press) in January 2014 now available
The CFP for the GECCO workshop that we are running in Problem-Understanding and Real-world optimisation (PURO) is now available. Note the deadline for paper submission is 28th March
Full details here: http://www.soc.napier.ac.uk/~cs378/PuroGECCO2014/index.html
to be held as part of the
2014 Genetic and Evolutionary Computation Conference (GECCO-2014)
Vancouver, BC, Canada, July 12-16, 2014
Submission Deadline : March 28th, 2014
See http://www.soc.napier.ac.uk/~cs378/PuroGECCO2014/index.html for submission details.
Accepted workshop papers are published in their own volume by ACM.
Building on the success of previous Understand Problems and Real-World Optimisation workshops, this workshop aims to provide a single forum for the presentation and discussion of works focused on optimisation problems rather than the methods for solving them. The workshop brings together the study of real-world optimisation problems with the theoretical analysis and synthesis of problems.
The workshop will focus on, but not be limited to, topics such as:
- Methods for identifying and constructing models for new optimisation problems
- Study of real-world optimisation problems and case studies
- Theoretical and practical analysis of optimisation problems
- Fitness landscape analysis of real-world problems
- Classification and ontological analysis of problems
- Development of and technologies for building benchmark test problems
- Technologies and theoretical works supporting the implementation, examination and
The workshop will run for half a day (2 sessions). We aim to hold a mixed workshop of invited talks (including at least one from industry) and paper presentations, ending with an open discussion. Authors will be invited to submit either an extended abstract or full paper, with more presentation time allocated to full paper submissions. Abstracts will also be invited from researchers wishing to provide demonstrations of software that address any of the themes of this workshop. To facilitate discussion of new ideas and approaches, authors will be encouraged to submit position papers which present new ideas for discussion or are of a conceptual nature. Papers will be accepted or rejected based on blind peer review conducted by our organising committee.
Papers should be formatted using the standard ACM templates and not exceed 8 pages. Formatting instructions can be found at http://www.sigevo.org/gecco-2014/papers.html Papers should be submitted by email to k(dot)sim(at)napier.ac.uk with the subject line GECCO WORKSHOP SUBMISSION no later than March 28 2014
Invited Talk (industry)
Invited Talk (academia)
Kent McClymont is an associate research fellow at the University of Exeter. His research is focused on the study of multi-objective hyper-heuristic methods for solving hard real-world optimisation problems with heterogeneous encodings and novel methods for evaluating heuristics through new test problems and methodologies. He has run two previous GECCO workshops on “Understanding Problems” and is a member of the AISB committee and oversees the AISB workshop series.
Kevin Sim is a research fellow at Edinburgh Napier University, Scotland, UK. He currently works on a large national EPSRC project (EP/J021628/1) entitled “Real World Optimisation with Life-Long Learning”. His interests lie in the field of hyper-heuristics and classification algorithms. He has previously co-chaired workshops on the subject of real world optimisation problems at GECCO and EvoStar.
Gabriela Ochoa is a Lecturer at the University of Stirling in Scotland. Her research interests lie in the foundations and application of evolutionary algorithms and heuristic search methods, with emphasis on autonomous (self-*) search and fitness landscape analysis. She has published over 60 international peer reviewed papers. She is associate editor of Evolutionary Computation (MIT Press), was involved in founding the Self-* Search track at GECCO, and has organised several workshops and special sessions at international conferences.
Ed Keedwell is a Senior Lecturer in Computer Science at the University of Exeter. His research is focused on Nature-Inspired Computation techniques and their application to real-world optimisation problems in engineering and bioinformatics. He has published over 70 papers in this field and currently leads a group of 8-10 postgraduate students and postdoctoral researchers. His currently funded EPSRC research includes ‘SEQAH’ (EP/K000519/1), a project investigating the interaction between selective hyper-heuristics, heuristics and problems over time.
Paper/Poster Submission: March 28 2014
Notification to Authors: April 15 2014
Camera ready Submission: April 25 2014
Conference Dates: July 12-16, 2014
Workshop Dates: T.B.A.
Workshop Website: http://www.soc.napier.ac.uk/~cs378/PuroGECCO2014/index.html
Conference website: http://www.sigevo.org/gecco-2014/
The ROLL team will be demonstrating their new software nicknamed NELLI at the SICSA Demofest in Glasgow on Tuesday 5th November.
Our goal is to develop an automated system for solving real optimisation problems that, like humans, continuously learns over time and improve its performance with experience. The resulting Network for Life Long Learning (NELLI) produces fast, high-quality solutions and adapts quickly to changing circumstances and problem characteristics. The efficient design of the system enables NELLI to cope with the complex constraints that characterise many real-world problem.
Key features of NELLI include:
- Automatically generated heuristics collaborate to optimise overall performance
- Using prior knowledge to quickly provide good quality solutions while continually adapting to new unseen problems
- Maintaining a memory that enables rapid production of solutions