Michael G. Epitropakis

Lancaster University — United Kingdom

Computer Science · Physical Sciences

17h-index1.8kcitations52works1.02yr avg
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Research Topics

Metaheuristic Optimization Algorithms Research(28), Evolutionary Algorithms and Applications(23), Advanced Multi-Objective Optimization Algorithms(21), Neural Networks and Applications(5), Music and Audio Processing(5)

Publications52 total

Hyper-heuristics
2025
Experimental Setup for GECCO 2024 Competition on Benchmarking Niching Methods for Multimodal Optimization
Proceedings of the Genetic and Evolutionary Computation Conference Companion·2024· 1 cited
New Tunable Test Problems for Benchmarking Niching Methods for Multimodal Optimization
Proceedings of the Genetic and Evolutionary Computation Conference·2024· 2 cited
A systematic approach to parameter optimization and its application to flight schedule simulation software
Journal of Heuristics·2022· 3 citedOpen Access
A hyper-heuristic approach based upon a hidden Markov model for the multi-stage nurse rostering problem
Computers & Operations Research·2021· 34 citedOpen Access
Metaheuristics for Finding Multiple Solutions
Natural computing series·2021· 13 cited
Multimodal Optimization: Formulation, Heuristics, and a Decade of Advances
Natural computing series·2021· 5 cited
Integer Weight Higher-Order Neural Network Training Using Distributed Differential Evolution
2019
HyperSPAM: A study on hyper-heuristic coordination strategies in the continuous domain
Information Sciences·2018· 51 citedOpen Access
Learning Without Peeking: Secure Multi-party Computation Genetic Programming
Lecture notes in computer science·2018· 2 citedOpen Access
Workshops at PPSN 2018
Lecture notes in computer science·2018
Hyper-heuristics
2018· 2 cited
Hyper-heuristics
2018· 3 cited
Tutorials at PPSN 2018
Lecture notes in computer science·2018
Progressive preference articulation for decision making in multi-objective optimisation problems
Integrated Computer-Aided Engineering·2017· 62 cited
A hybrid breakout local search and reinforcement learning approach to the vertex separator problem
European Journal of Operational Research·2017· 19 citedOpen Access
Seeking Multiple Solutions: An Updated Survey on Niching Methods and Their Applications
IEEE Transactions on Evolutionary Computation·2016· 328 cited
Results of the 2015 IEEE CEC Competition on Niching Methods for Multimodal Optimization
2016· 7 cited
Tutorials at PPSN 2016
Lecture notes in computer science·2016
Tutorials at PPSN 2016
Lancaster EPrints (Lancaster University)·2016Open Access
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Frequent Co-authors

Michael N. Vrahatis(22), Vassilis P. Plagianakos(16), Edmund Burke(10), Xiaodong Li(8), Mike Preuß(7), Μάξιμος Καλιακάτσος-Παπακώστας(6), Nicos G. Pavlidis(4), Jonathan E. Fieldsend(4), Andries P. Engelbrecht(3), Dimitris K. Tasoulis(3), Shin Yoo(3), Ferrante Neri(3), Jerry Swan(3), Alexander E. I. Brownlee(3), Andreas Floros(3), Julian F. Miller(3), Pietro S. Oliveto(3), Giovanni Squillero(3), Alberto Tonda(3), Mark Harman(2)