Computational Optimisation and Learning (COL) Lab
 

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Ender Özcan

Professor of Computer Science and Operational Research, Faculty of Science

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Biography

Ender Özcan is a Professor of Computer Science and Operational Research with the Computational Optimisation and Learning (COL) Lab in the School of Computer Science at the University of Nottingham, UK (UoN). He received his PhD from the Department of Computer and Information Science at Syracuse University, NY, USA in 1998. He worked as a lecturer in the Department of Computer Engineering at Yeditepe University, Istanbul, Turkiye from 1998-2007. He established and led the ARTIficial Intelligence research group from 2002. He served as the Deputy Head of the Department from 2004-2007. Prof Özcan was appointed as a senior research fellow in 2008 to the EPSRC funded LANCS initiative, one of the largest Science and Innovation Rewards given by EPSRC (Engineering and Physical Sciences Research Council, UK). He has been an academic at the University of Nottingham since then. He is currently Director of the Faculty of Science Doctoral Training Centre in Artificial Intelligence.

Prof Özcan is an internationally-leading scientist in computational optimisation for intelligent decision support, underpinned by hyper-heuristics/metaheuristics combined with data science, tackling challenging real-world problems. His pioneering work at the interface of Computer Science, Artificial Intelligence and Operational Research has been extensively exploited and extended by other researchers, resulting in high number of citations, plenaries/keynotes at conferences, invited talks/guest lectures and tutorials. Currently, he is ranked within the World's top 2% scientists in Artificial Intelligence based on a recent study by Elsevier BV and Stanford University. Prof Özcan has over 150 refereed publications at reputable venues.

He served as an Executive Committee member for the LANCS initiative. He was the Deputy Director of the EPSRC's National Taught Course Centre in Operational Research (NATCOR). He is a Senior Member of IEEE, an elected member of the EPSRC, and College Research Foundation - Flanders (FWO) Peer Review College. Prof Özcan contributed and has been contributing to the funded projects worth over £14m in total to date as principal investigator and co-investigator/named researchers, supported by various funding bodies, including the EPSRC, European Commission, The Royal Society, TSB, Innovate UK and TUBITAK. Prof Özcan is a co-founder and co-chair of the EURO Working Group on Data Science Meets Optimisation. He is Associate Editor of the Journal of Scheduling and International Journal of Applied Metaheuristic Computing, and on the Editorial (Advisory) Board of the Engineering Applications of Artificial Intelligence (EAAI) Journal and International Journal of Intelligent Computing and Cybernetics. He is Steering Committee member and Executive Officer of the International Conference Series on the Practice and Theory of Automated Timetabling (PATAT).

Expertise Summary

My expertise lies at the interface of Computer Science, Artificial Intelligence (AI) and Operational Research, with a focus on intelligent decision support systems embedding data science, mainly machine learning and heuristic,hyper-heuristic and metaheuristic optimisation techniques applied to real-world optimisation problems.

Keywords: artificial intelligence, optimisation, intelligent decision support, heuristic, metaheuristic, hyper-heuristic, evolutionary algorithm, adaptive approaches, timetabling, cutting and packing

Teaching Summary

I have been teaching informed by my research and scholarly activities exploiting my industrial links, and leading teaching innovation through the development and delivery of the undergraduate… read more

Research Summary

My research interests and activities lie at the interface of artificial intelligence, computer science, and operational research: Intelligent decision support systems, search and optimisation,… read more

Selected Publications

I have been teaching informed by my research and scholarly activities exploiting my industrial links, and leading teaching innovation through the development and delivery of the undergraduate courses, specifically:

  • Artificial Intelligence Methods that trails cutting-edge optimisation, namely metaheuristic and hyper-heuristic techniques into the Computer Science curriculum to provide students with an invaluable background and set of skills building on our strengths in this AI field within the School, and
  • Level 3&4 Projects (each being a key component of the degree) that apply an innovative assessment framework and student engagement activities for enhanced student experience driven by continual student feedback.

Current Research

My research interests and activities lie at the interface of artificial intelligence, computer science, and operational research: Intelligent decision support systems, search and optimisation, including combinatorial optimisation, constraint optimisation, multi-modal optimisation and multi-objective optimisation using heuristics, local search, hyper-heuristics, metaheuristics, in particular memetic algorithms, particle swarm optimisation, hybrid approaches embedding data science techniques and their theoretical foundations.

Modelling of and applications to the complex real-world problems, including scheduling, timetabling, cutting&packing, SAT, knapsack problems, TSP, VRP and more, that are at the boundary of artificial intelligence, computer science and operational research, including grouping problems, such as, data clustering, graph colouring and bin packing.

  • SONG, H., DENG, B., POUND, M., ÖZCAN, E. and TRIGUERO, I., 2022. A fusion spatial attention approach for few-shot learning Information Fusion. 81, 187-202
  • DEVECI, M., ÖNER, S.C., CIFTCI, M.E., ÖZCAN, E. and PAMUCAR, D., 2022. Interval type-2 hesitant fuzzy Entropy-based WASPAS approach for aircraft type selection Applied Soft Computing. 114, 108076
  • JERRY SWAN, STEVEN ADRIAENSEN, ALEXANDER E.I. BROWNLEE, KEVIN HAMMOND, COLIN G. JOHNSON, AHMED KHEIRI, FAUSTYNA KRAWIEC, J.J. MERELO, LEANDRO L. MINKU, ENDER ÖZCAN, GISELE L. PAPPA, PABLO GARCÍA-SÁNCHEZ, KENNETH SÖRENSEN, STEFAN VOß, MARKUS WAGNER and DAVID R. WHITE, 2022. Metaheuristics “In the Large” European Journal of Operational Research. 297(2), 393-406
  • DELIKTAŞ, D., ÖZCAN, E., USTUN, O. and TORKUL, O., 2021. Evolutionary algorithms for multi-objective flexible job shop cell scheduling Applied Soft Computing. 113, 107890
  • RAMAMOORTHY, V.T., ÖZCAN, E., PARKES, A.J., SREEKUMAR, A., JAOUEN, L. and BÉCOT, F.-X., 2021. Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials Journal of the Acoustical Society of America. 150(4), 3164-3175
  • CARVALHO, V.R., ÖZCAN, E. and SICHMAN, J.S., 2021. Comparative analysis of selection hyper-heuristics for real-world multi-objective optimization problems Applied Sciences (Switzerland). 11(19), 9153
  • DEVECI, M., ÖZCAN, E., JOHN, R., PAMUCAR, D. and KARAMAN, H., 2021. Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS Applied Soft Computing. 109, 107532
  • ÖZCAN, E., BURKE, E.K., DI GASPERO, L., MCCOLLUM, B. and MUSLIU, N., 2021. Preface: The practice and theory of automated timetabling (2018) Annals of Operations Research. 302(2), 339-340
  • SONG, H., TORRES TORRES, M., ÖZCAN, E. and TRIGUERO, I., 2021. L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout Neurocomputing. 442, 200-208
  • TÜRK, S., DEVECI, M., ÖZCAN, E., CANITEZ, F. and JOHN, R., 2021. Interval type-2 fuzzy sets improved by Simulated Annealing for locating the electric charging stations Information Sciences. 547, 641-666
  • SWAN, J., ADRIAENSEN, S., BROWNLEE, A.E.I., HAMMOND, K., JOHNSON, C.G., KHEIRI, A., KRAWIEC, F., MERELO, J.J., MINKU, L.L., ÖZCAN, E., PAPPA, G.L., GARCÍA-SÁNCHEZ, P., SÖRENSEN, K., VOß, S., WAGNER, M. and WHITE, D.R., 2021. Metaheuristics “In the Large” European Journal of Operational Research.
  • TÜRK, S., ÖZCAN, E. and JOHN, R., 2021. Many-objective Optimisation for an Integrated Supply Chain Management Problem Studies in Fuzziness and Soft Computing. 403, 97-111
  • JOHN H. DRAKE, AHMED KHEIRI, ENDER OZCAN and EDMUND K. BURKE, 2020. Recent advances in selection hyper-heuristics European Journal of Operational Research. 285(2), 405-428
  • TAYMAZ RAHKAR FARSHI, JOHN H. DRAKE and ENDER OZCAN, 2020. A multimodal particle swarm optimization-based approach for image segmentation Expert Systems with Applications. 149, 113233
  • DEVECI, M., ÖZCAN, E., JOHN, R., COVRIG, C.-F. and PAMUCAR, D., 2020. A study on offshore wind farm siting criteria using a novel interval-valued fuzzy-rough based Delphi method Journal of Environmental Management. 270, 110916
  • SANTIAGO JÚNIOR, V.A.D., ÖZCAN, E. and CARVALHO, V.R.D., 2020. Hyper-Heuristics based on Reinforcement Learning, Balanced Heuristic Selection and Group Decision Acceptance Applied Soft Computing Journal. 97, 106760
  • ARAÚJO, L.J.P., PANESAR, A., ÖZCAN, E., ATKIN, J., BAUMERS, M. and ASHCROFT, I., 2020. An experimental analysis of deepest bottom-left-fill packing methods for additive manufacturing International Journal of Production Research. 58(22), 6917-6933
  • KHEIRI, A., AHMED, L., BOYACI, B., GROMICHO, J., MUMFORD, C., ÖZCAN, E. and DIRIKOÇ, A.S., 2020. Exact and hyper-heuristic solutions for the distribution-installation problem from the VeRoLog 2019 challenge Networks. 76(2), 294-319
  • ARAÚJO, L.J.P., PANESAR, A., ÖZCAN, E., ATKIN, J., BAUMERS, M. and ASHCROFT, I., 2019. An experimental analysis of deepest bottom-left-fill packing methods for additive manufacturing International Journal of Production Research.
  • ARAÚJO, L.J.P., ÖZCAN, E., ATKIN, J.A.D. and BAUMERS, M., 2019. Analysis of irregular three-dimensional packing problems in additive manufacturing: a new taxonomy and dataset International Journal of Production Research. 57(18), 5920-5934
  • HEDA SONG, ISAAC TRIGUERO and ENDER OZCAN, 2019. A review on the self and dual interactions between machine learning and optimisation Progress in Artificial Intelligence. 8(2), 143-165
  • LI, WENWEN, ÖZCAN, ENDER and JOHN, ROBERT, 2019. A Learning Automata-Based Multiobjective Hyper-Heuristic IEEE Transactions on Evolutionary Computation. 23(1), 59-73
  • KHAJAVI, S.H., BAUMERS, M., HOLMSTRÖM, J., ÖZCAN, E., ATKIN, J., JACKSON, W. and LI, W., 2018. To kit or not to kit: Analysing the value of model-based kitting for additive manufacturing Computers in Industry. 98, 100-117
  • WILSON, DENNIS, RODRIGUES, SILVIO, SEGURA, CARLOS, LOSHCHILOV, ILYA, HUTTER, FRANK, LOPEZ BUENFIL, GUILLERMO, KHEIRI, AHMED, KEEDWELL, ED, OCAMPO-PINEDA, MARIO, OZCAN, ENDER, VALDEZ PENA, SERGIO IVVAN, GOLDMAN, BRIAN, BOTELLO RIONDA, SALVADOR, HERNANDEZ-AGUIRRE, ARTURO, VEERAMACHANENI, KALYAN and CUSSAT-BLANC, SYLVAIN, 2018. Evolutionary computation for wind farm layout optimization Renewable Energy. 126, 681-691
  • HONG, LIBIN, DRAKE, JOHN H., WOODWARD, JOHN R. and OZCAN, ENDER, 2018. A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming Applied Soft Computing. 62, 162-175
  • WARREN G. JACKSON, ENDER ÖZCAN and ROBERT I. JOHN, 2018. Move acceptance in local search metaheuristics for cross-domain search Expert Systems with Applications. 109, 131-151
  • TÜRK, SEDA, ÖZCAN, ENDER and JOHN, ROBERT, 2017. Multi-objective optimisation in inventory planning with supplier selection Expert Systems with Applications. 78, 51-63
  • MUKLASON, AHMAD, PARKES, ANDREW J., OZCANA, ENDER, MCCOLLUM, BARRY and MCMULLAN, PAUL, 2017. Fairness in examination timetabling: Student preferences and extended formulations APPLIED SOFT COMPUTING. 55, 302-318
  • LI, WENWEN, OZCAN, ENDER and JOHN, ROBERT, 2017. Multi-objective evolutionary algorithms and hyper-heuristics for wind farm layout optimisation RENEWABLE ENERGY. 105, 473-482
  • NELISHIA PILLAY and ENDER OZCAN, 2017. Automated generation of constructive ordering heuristics for educational timetabling Annals of Operations Research. 275(1), 181-208
  • JOHN DRAKE, ENDER OZCAN and EDMUND K BURKE, 2016. A Case Study of Controlling Crossover in a Selection Hyper-heuristic Framework using the Multidimensional Knapsack Problem Evolutionary Computation. 24(1), 113-141
  • KHEIRI, AHMED and ÖZCAN, ENDER, 2016. An iterated multi-stage selection hyper-heuristic European Journal of Operational Research. 250(1), 77-90
  • SORIA-ALCARAZ, JORGE A, ÖZCAN, ENDER, SWAN, JERRY, KENDALL, GRAHAM and CARPIO, MARTIN, 2016. Iterated local search using an add and delete hyper-heuristic for university course timetabling Applied Soft Computing. 40, 581-593
  • SIMON MARTIN, DJAMILA OUELHADJ, PATRICK BEULLENS, ENDER ÖZCAN, ANGEL A. JUAN and EDMUND K. BURKE, 2016. A multi-agent based cooperative approach to scheduling and routing European Journal of Operational Research. 254(1), 169-178
  • SHAHRIAR ASTA, DANIEL KARAPETYAN, AHMED KHEIRI, ENDER ÖZCAN and ANDREW J. PARKES, 2016. Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem Information Sciences. 373, 476 - 498
  • ENDER ÖZCAN, JOHN H. DRAKE, CEVRIYE ALTINTAŞ and SHAHRIAR ASTA, 2016. A Self-adaptive Multimeme Memetic Algorithm Co-evolving Utility Scores to Control Genetic Operators and Their Parameter Settings Applied Soft Computing. 49, 81–93
  • ASTA, SHAHRIAR, OZCAN, ENDER and PARKES, ANDREW J., 2016. CHAMP: Creating heuristics via many parameters for online bin packing EXPERT SYSTEMS WITH APPLICATIONS. 63, 208-221
  • ASTA, SHAHRIAR, OZCAN, ENDER and CURTOIS, TIM, 2016. A tensor based hyper-heuristic for nurse rostering KNOWLEDGE-BASED SYSTEMS. 98, 185-199
  • KHEIRI, AHMED, OEZCAN, ENDER and PARKES, ANDREW J., 2016. A stochastic local search algorithm with adaptive acceptance for high-school timetabling ANNALS OF OPERATIONS RESEARCH. 239(1), 135-151
  • SHAHRIAR ASTA and ENDER OZCAN, 2015. A Tensor-based Selection Hyper-heuristic for Cross-domain Heuristic Search Information Sciences. 299, 412–432
  • H MUJTABA, G KENDALL, R BAIG and E OZCAN, 2015. Detecting Change and Dealing with Uncertainty in Imperfect Evolutionary Environments Information Sciences. 302, 33-49
  • M. MAASHI, G. KENDALL and E. 'OZCAN, 2015. Choice Function based Hyper-heuristics for Multi-objective Optimization Applied Soft Computing. 28, 312-326
  • DRAKE, JOHN H, ÖZCAN, ENDER and BURKE, EDMUND K, 2015. Modified choice function heuristic selection for the multidimensional knapsack problem. In: Genetic and Evolutionary Computing Springer International Publishing. 225-234
  • TURK, SEDA, MILLER, SIMON, OZCAN, ENDER and JOHN, ROBERT, 2015. A simulated annealing approach to supplier selection aware inventory planning In: Evolutionary Computation (CEC), 2015 IEEE Congress on. 1799-1806
  • DRAKE, JOHN H, OZCAN, ENDER and BURKE, EDMUND K, 2015. A modified choice function hyper-heuristic controlling unary and binary operators In: Evolutionary Computation (CEC), 2015 IEEE Congress on. 3389-3396
  • ASTA, SHAHRIAR and OZCAN, ENDER, 2015. A tensor analysis improved genetic algorithm for online bin packing In: Proceedings of the 2015 on Genetic and Evolutionary Computation Conference. 799-806
  • ELHAG, ANAS and ÖZCAN, ENDER, 2015. A grouping hyper-heuristic framework: Application on graph colouring Expert Systems with Applications. 42(13), 5491-5507
  • DRAKE, JOHN H, OZCAN, ENDER and BURKE, EDMUND K, 2015. A comparison of crossover control mechanisms within single-point selection hyper-heuristics using HyFlex In: Evolutionary Computation (CEC), 2015 IEEE Congress on. 3397-3403
  • ARAÚJO, LUIZ JONATA P, ÖZCAN, ENDER, ATKIN, JASON AD, BAUMERS, MARTIN, TUCK, CHRIS and HAGUE, RICHARD, 2015. Toward Better Build Volume Packing In Additive Manufacturing: Classification Of Existing Problems And Benchmarks
  • BURKE, EDMUND K, DRAKE, JOHN H, MCCOLLUM, BARRY, ÖZCAN, ENDER and OTHERS, 2015. Comments on: An overview of curriculum-based course timetabling TOP: An Official Journal of the Spanish Society of Statistics and Operations Research. 23(2), 355-358
  • AHMED, LEENA N, ÖZCAN, ENDER and KHEIRI, AHMED, 2015. Solving high school timetabling problems worldwide using selection hyper-heuristics Expert Systems with Applications. 42(13), 5463-5471
  • DEVECI, MUHAMMET, DEMIREL, NIHAN ÇETIN, JOHN, ROBERT and ÖZCAN, ENDER, 2015. Fuzzy multi-criteria decision making for carbon dioxide geological storage in Turkey Journal of Natural Gas Science and Engineering. 27, 692-705
  • MAASHI, MASHAEL, KENDALL, GRAHAM and ÖZCAN, ENDER, 2015. Choice function based hyper-heuristics for multi-objective optimization Applied Soft Computing. 28, 312-326
  • BURKE, EDMUND K, DRAKE, JOHN H, MCCOLLUM, BARRY, ÖZCAN, ENDER and OTHERS, 2015. Comments on: An overview of curriculum-based course timetabling TOP: An Official Journal of the Spanish Society of Statistics and Operations Research. 23(2), 355-358
  • SYARIZA ABDUL RAHMAN, ANDRZEJ BARGIELA, EDMUND K. BURKE, ENDER ÖZCAN, BARRY MCCOLLUM and PAUL MCMULLAN,, 2014. Adaptive linear combination of heuristic orderings in constructing examination timetables European Journal of Operational Research. 232(2), 287 - 297
  • MASHAEL MAASHI, ENDER ÖZCAN and GRAHAM KENDALL,, 2014. A multi-objective hyper-heuristic based on choice function Expert Systems with Applications. 41(9), 4475 - 4493
  • HONG, LIBIN, DRAKE, JOHN H. and ÖZCAN, ENDER, 2014. A Step Size Based Self-adaptive Mutation Operator for Evolutionary Programming In: Proceedings of the 2014 Conference Companion on Genetic and Evolutionary Computation Companion. 1381-1388
  • BROWNLEE, ALEXANDER E.I., SWAN, JERRY, ÖZCAN, ENDER and PARKES, ANDREW J., 2014. Hyperion2: A Toolkit for Meta-, Hyper- Heuristic Research In: Proceedings of the 2014 Conference Companion on Genetic and Evolutionary Computation Companion. 1133-1140
  • DULCE J. MAGANA-LOZANO, E. 'OZCAN and S. E. CONANT-PABLOS, 2014. Decomposition and Recomposition Strategies to Solve Timetabling Problems In: Proceedings of the 10th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2014). 505-507
  • A. MUKLASON, A. J. PARKES, B. MCCOLLUM and E. 'OZCAN, 2014. Fairness in Examination Timetabling: Student Preferences and Extended Formulations In: Proceedings of the 10th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2014). 512-515
  • C. ALTINTAS, S.ASTA, E. 'OZCAN and T. YIGIT, 2014. A self-generating memetic algorithm for examination timetabling In: Proceedings of the 10th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2014). 434-437
  • S. ASTA and E. ÖZCAN, 2014. A Tensor-based Approach to Nurse Rostering In: Proceedings of the 10th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2014). 442-445,
  • SWAN, JERRY, WOODWARD, JOHN, ÖZCAN, ENDER, KENDALL, GRAHAM and BURKE, EDMUND, 2014. Searching the Hyper-heuristic Design Space Cognitive Computation. 6(1), 66-73
  • AHMED KHEIRI and ENDER ÖZCAN, 2014. Constructing Constrained-Version of Magic Squares Using Selection Hyper-heuristics The Computer Journal. 57(3), 469-479
  • ERCAL, T., 'OZCAN, E. and ASTA, S., 2014. Soft Morphological Filter Optimization Using a Genetic Algorithm for Noise Elimination In: 14th UK Workshop on Computational Intelligence, UKCI 2014. 1-7
  • TURK, S., JOHN, R. I., 'OZCAN, E. and ASTA, S., 2014. Interval Type-2 Fuzzy Sets in Supplier Selection In: 14th UK Workshop on Computational Intelligence, UKCI 2014. 1-7
  • JACKSON, W. G., 'OZCAN, E. and JOHN, R. I., 2014. Fuzzy Adaptive Parameter Control of a Late Acceptance Hyper-heuristic In: 14th UK Workshop on Computational Intelligence, UKCI 2014. 1-8
  • YARIMCAM, AHMET, ASTA, SHAHRIAR, 'OZCAN, ENDER and PARKES, ANDREW J., 2014. Heuristic generation via parameter tuning for online bin packing In: Evolving and Autonomous Learning Systems (EALS), 2014 IEEE Symposium on. 102-108
  • ASTA, SHAHRIAR and 'OZCAN, ENDER, 2014. An apprenticeship learning hyper-heuristic for vehicle routing in HyFlex In: Evolving and Autonomous Learning Systems (EALS), 2014 IEEE Symposium on. 65-72
  • ASTA, S., 'OZCAN, E. and SIEBERS, P.-O., 2014. An Investigation on Test Driven Discrete Event Simulation In: The Operational Research Society Simulation Workshop 2014. 1-11
  • DRAKE, JOHN H, HYDE, MATTHEW, IBRAHIM, KHALED and OZCAN, ENDER, 2014. A genetic programming hyper-heuristic for the multidimensional knapsack problem Kybernetes. 43(9/10), 1500-1511
  • ABDUL-RAHMAN, SYARIZA, BURKE, EDMUND K., BARGIELA, ANDRZEJ, MCCOLLUM, BARRY and 'OZCAN, ENDER, 2014. A constructive approach to examination timetabling based on adaptive decomposition and ordering Annals of Operations Research. 218(1), 3-21
  • ÖZCAN, E., KAI, Z. and DRAKE, J.H., 2013. Bidirectional best-fit heuristic considering compound placement for two dimensional orthogonal rectangular strip packing Expert Systems with Applications. 40(10), 4035–4043
  • MARTIN, S., OUELHADJ, D., SMET, P., VANDEN BERGHE, G. and ÖZCAN, E., 2013. Cooperative search for fair nurse rosters Expert Systems with Applications. 40(16), 6674-6683
  • ORTIZ-BAYLISS, J.C., 'OZCAN, E., PARKES, A.J. and TERASHIMA-MARIN, H., 2013. A genetic programming hyper-heuristic: Turning features into heuristics for constraint satisfaction In: 13th UK Workshop on Computational Intelligence, UKCI 2013. 183-190
  • OZCAN, E., ASTA, S. and ALTINTAS, C., 2013. Memetic algorithms for Cross-domain Heuristic Search In: 13th UK Workshop on Computational Intelligence, UKCI 2013. 175-182
  • OZCAN, E., MISIR, M. and KHEIRI, A., 2013. Group decision making hyper-heuristics for function optimisation In: 13th UK Workshop on Computational Intelligence, UKCI 2013. 327-333
  • ELHAG, A. and 'OZCAN, E., 2013. A grouping hyper-heuristic framework based on linear linkage encoding for graph coloring In: 13th UK Workshop on Computational Intelligence, UKCI 2013. 321-326
  • JACKSON, W.G., 'OZCAN, E. and DRAKE, J.H., 2013. Late acceptance-based selection hyper-heuristics for cross-domain heuristic search In: 13th UK Workshop on Computational Intelligence, UKCI 2013. 228-235
  • ASTA, S., 'OZCAN, E. and PARKES, A.J., 2013. Batched mode hyper-heuristics. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7997. 404-409
  • KIRAZ, B., ETANER-UYAR, A.S. and 'OZCAN, E., 2013. Selection hyper-heuristics in dynamic environments Journal of the Operational Research Society. 64(12), 1753-1769
  • KALENDER, M., KHEIRI, A., 'OZCAN, E. and BURKE, E.K., 2013. A greedy gradient-simulated annealing selection hyper-heuristic Soft Computing. 17(12), 2279-2292
  • ULUDAG, G., KIRAZ, B., ETANER-UYAR, S. and 'OZCAN, E., 2013. A hybrid multi-population framework for dynamic environments combining online and offline learning Soft Computing. 17(12), 2327-2348
  • BURKE, E.K., GENDREAU, M., HYDE, M., KENDALL, G., OCHOA, G., 'OZCAN, E. and QU, R., 2013. Hyper-heuristics: A survey of the state of the art Journal of the Operational Research Society. 64(12), 1695-1724
  • SWAN, J., DRAKE, J., 'OZCAN, E., GOULDING, J. and WOODWARD, J., 2013. A comparison of acceptance criteria for the daily car-pooling problem. In: Computer and Information Sciences III - 27th International Symposium on Computer and Information Sciences, ISCIS 2012 477-483
  • ASTA, S., 'OZCAN, E. and PARKES, A.J., 2013. Dimension reduction in the search for online bin packing policies. In: GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion 65-66
  • ORTIZ-BAYLISS, J.C., TERASHIMA-MARIN, H., 'OZCAN, E., PARKES, A.J. and CONANT-PABLOS, S.E., 2013. Exploring heuristic interactions in constraint satisfaction problems: A closer look at the hyper-heuristic space In: Proceddings of the IEEE Congress on Evolutionary Computation, CEC 2013. 3307-3314
  • ETANER-UYAR, S., 'OZCAN, E. and URQUHART, N., 2013. Preface. In: Studies in Computational Intelligence 505.
  • LEHRE, P.K. and 'OZCAN, E., 2013. A runtime analysis of simple hyper-heuristics: To mix or not to mix operators In: FOGA 2013 - Proceedings of the 12th ACM Workshop on Foundations of Genetic Algorithms. 97-104
  • KIRAZ, B., ETANER-UYAR, A.S. and 'OZCAN, E., 2013. An ant-based selection hyper-heuristic for dynamic environments. In: 7835. 626-635
  • KHEIRI, A. and 'OZCAN, E., 2013. A hyper-heuristic with a round robin neighbourhood selection. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7832. 1-12
  • ASTA, S., 'OZCAN, E., PARKES, A.J. and ETANER-UYAR, A.S., 2013. Generalizing hyper-heuristics via apprenticeship learning. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7832. 169-178
  • HONG, L., WOODWARD, J., LI, J. and 'OZCAN, E., 2013. Automated design of probability distributions as mutation operators for evolutionary programming using genetic programming. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7831. 85-96
  • DRAKE, J.H., KILILIS, N. and 'OZCAN, E., 2013. Generation of VNS components with grammatical evolution for vehicle routing. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7831. 25-36
  • 2013. Automated Scheduling and Planning: From Theory to Practice Springer.
  • ÖZCAN, E., PARKES, A.J. and ALKAN, A., 2012. The interleaved constructive memetic algorithm and its application to timetabling Computers & Operations Research. 39(10), 2310–2322
  • ULUDAG, G., KIRAZ, B., ETANER UYAR, A.S. and 'OZCAN, E., 2012. Heuristic selection in a multi-phase hybrid approach for dynamic environments In: 12th UK Workshop on Computational Intelligence, UKCI 2012.
  • K'OLE, M., SIMA ETANER-UYAR, A., KIRAZ, B. and 'OZCAN, E., 2012. Heuristics for car setup optimisation in TORCS In: 12th UK Workshop on Computational Intelligence, UKCI 2012.
  • KALENDER, M., KHEIRI, A., 'OZCAN, E. and BURKE, E.K., 2012. A greedy gradient-simulated annealing hyper-heuristic for a curriculum-based course timetabling problem In: 12th UK Workshop on Computational Intelligence, UKCI 2012.
  • ULUDAG, G., KIRAZ, B., ETANER-UYAR, A.S. and 'OZCAN, E., 2012. A framework to hybridize PBIL and a hyper-heuristic for dynamic environments 7492(PART 2), 358-367
  • OZCAN, E. and KHEIRI, A., 2012. A hyper-heuristic based on random gradient, greedy and dominance In: Computer and Information Sciences II - 26th International Symposium on Computer and Information Sciences, ISCIS 2011. 557-563
  • DRAKE, J.H., 'OZCAN, E. and BURKE, E.K., 2012. An improved choice function heuristic selection for cross domain heuristic search. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7492. 307-316
  • ORTIZ-BAYLISS, J.C., TERASHIMA-MARÍN, H., CONANT-PABLOS, S.E., 'OZCAN, E. and PARKES, A.J., 2012. Improving the performance of vector hyper-heuristics through local search In: GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation. 1269-1276
  • PARKES, A.J., 'OZCAN, E. and HYDE, M.R., 2012. Matrix analysis of genetic programming mutation. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7244. 158-169
  • SWAN, J., ÖZCAN, E. and KENDALL, G., 2011. Hyperion-a recursive hyper-heuristic framework In: Learning and Intelligent Optimization, 5th International Conference, LION.
  • ORTIZ-BAYLISS, J.C., TERASHIMA-MARÍN, H., ÖZCAN, E. and PARKES, A.J., 2011. On the idea of evolving decision matrix hyper-heuristics for solving constraint satisfaction problems In: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation. 255-256
  • KIRAZ, B., UYAR, A. and ÖZCAN, E., 2011. An investigation of selection hyper-heuristics in dynamic environments In: Applications of Evolutionary Computation. 314-323
  • ORTIZ-BAYLISS, JOSÉCARLOS, TERASHIMA-MARÍN, HUGO, ÖZCAN, ENDER, PARKES, ANDREWJ. and CONANT-PABLOS, SANTIAGOENRIQUE, 2011. Variable and Value Ordering Decision Matrix Hyper-heuristics: A Local Improvement Approach. In: BATYRSHIN, ILDAR and SIDOROV, GRIGORI, eds., Advances in Artificial Intelligence 7094. Springer Berlin Heidelberg. 125-136
  • ÖZCAN, E. and PARKES, A.J., 2011. Policy matrix evolution for generation of heuristics In: GECCO '11: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation. 2011-2018
  • BURKE, E.K., KENDALL, G., MISIR, M. and ÖZCAN, E., 2010. Monte Carlo hyper-heuristics for examination timetabling Annals of Operations Research. 196(1), 73-90
  • ÖZCAN,E., MISIR , M., OCHOA, G. and BURKE, E. K., 2010. A Reinforcement Learning - Great-Deluge Hyper-heuristic for Examination Timetabling International Journal of Applied Metaheuristic Computing. 1(1), 39-59
  • GIBBS, J., KENDALL , G. and ÖZCAN, E., 2010. Scheduling English Football Fixtures over the Holiday Period Using Hyper-heuristics. In: Lecture Notes in Computer Science: 11th International Conference on Parallel Problem Solving From Nature 6238. 496-505
  • OCHOA, G and OZCAN, E, 2010. Special Issue On Hyper-Heuristics In Search And Optimization Journal Of Heuristics. 16(6), 745-748
  • BURKE, E.K., HYDE, M., KENDALL, G., OCHOA, G., ÖZCAN, E. and WOODWARD, J.R., 2010. A classification of hyper-heuristic approaches Handbook of Metaheuristics. 449-468
  • ÖZCAN, E., MISIR, M., OCHOA, G. and BURKE, E.K., 2010. A reinforcement learning-greatdeluge hyper-heuristic for examination timetabling International Journal of Applied Metaheuristic Computing. 1(1), 39-59
  • ORTIZ-BAYLISS, J.C., OZCAN, E., PARKES, A.J. and TERASHIMA-MARÍN, H., 2010. Mapping the performance of heuristics for constraint satisfaction In: Evolutionary Computation (CEC), 2010 IEEE Congress on. 1-8
  • ÖZCAN, E. and BAŞARAN, C., 2009. A case study of memetic algorithms for constraint optimization Soft Computing. 13(8-9), 871-882
  • ÖZCAN, E., BYKOV, Y, BIRBEN, M. and BURKE, E. K., 2009. Examination Timetabling Using Late Acceptance Hyper-heuristics In: IEEE Congress on Evolutionary Computation (CEC 2009). 997-1004
  • AŞIK, O.B. and ÖZCAN, E., 2009. Bidirectional best-fit heuristic for orthogonal rectangular strip packing Annals of Operations Research. 172(1), 405-427
  • BURKE, E.K., HYDE, M.R., KENDALL, G., OCHOA, G., OZCAN, E. and WOODWARD, J.R., 2009. Exploring hyper-heuristic methodologies with genetic programming. In: Computational Intelligence Springer. 177-201
  • OZCAN, E., UYAR, S.E. and BURKE, E., 2009. A greedy hyper-heuristic in dynamic environments In: Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers. 2201-2204
  • OUELHADJ, D., PETROVIC, S. and OZCAN, E., 2009. A multi-level search framework for asynchronous cooperation of multiple hyper-heuristics In: Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers. 2193-2196
  • ÖZCAN, E., BILGIN, B. and KORKMAZ, E.E., 2008. A comprehensive analysis of hyper-heuristics Intelligent Data Analysis. 12(1), 3-23
  • BURKE, E. K., KENDALL, G., MISIR, M. and ÖZCAN, E., 2008. A Study of Simulated Annealing Hyperheuristics In: 7th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2008). 1-4
  • BURKE, E. K., MISIR, M., OCHOA, G. and ÖZCAN, E., 2008. Learning Heuristic Selection in Hyperheuristics for Examination Timetabling In: 7th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2008). 1-4
  • ÖZCAN, E. and ERÇAL, T., 2008. A genetic algorithm for generating improvised music In: Artificial Evolution. 266-277
  • ÜLKER, Ö., KORKMAZ, E. and ÖZCAN, E., 2008. A grouping genetic algorithm using linear linkage encoding for bin packing In: Parallel Problem Solving from Nature-PPSN X. 1140-1149
  • OZCAN, E and ONBASIOGLU, E, 2007. Memetic Algorithms For Parallel Code Optimization International Journal Of Parallel Programming. 35(1), 33-61
  • BILGIN, B., ÖZCAN, E. and KORKMAZ, E., 2007. An experimental study on hyper-heuristics and exam timetabling Practice and Theory of Automated Timetabling VI. 394-412
  • ERSOY, E., ÖZCAN, E. and UYAR, CS., 2007. Memetic algorithms and hyperhill-climbers MISTA. 7, 159-166
  • ÖZCAN, E. and ALKAN, A., 2007. A memetic algorithm for solving a timetabling problem: An incremental strategy In: Proc. of the 3rd multidisciplinary int. conf. on scheduling: theory and applications. 394-401
  • DIBEKLIOGLU, H., SEZGIN, T.M. and OZCAN, E., 2007. A recognizer for free-hand graph drawings In: Pen-Based Learning Technologies, 2007. PLT 2007. First International Workshop on. 1-3
  • OZCAN, E, BILGIN, B and KORKMAZ, EE, 2006. Hill Climbers And Mutational Heuristics In Hyperheuristics
  • ÖZCAN, E., BILGIN, B. and KORKMAZ, E., 2006. Hill climbers and mutational heuristics in hyperheuristics Parallel Problem Solving from Nature-PPSN IX. 202-211
  • ÖZCAN, E., 2006. Memes, self-generation and nurse rostering In: Proceedings of the 6th international conference on Practice and theory of automated timetabling VI. 85-104
  • OZCAN, E, 2005. Memetic Algorithms For Nurse Rostering
  • ÖZCAN, E., 2005. Memetic algorithms for nurse rostering Computer and Information Sciences-ISCIS 2005. 482-492
  • ÖZCAN, E., 2005. Towards an XML-based standard for timetabling problems: TTML Multidisciplinary Scheduling: Theory and Applications. 163-185
  • OZCAN, E. and ERSOY, E., 2005. Final exam scheduler-FES In: Evolutionary Computation, 2005. The 2005 IEEE Congress on. 1356-1363
  • ÖZCAN, E., CSEKER, CS.E. and KARADENİZ, Z.I., 2004. Generating Java Class Skeleton Using a Natural Language Interface In: NLUCS 2004. 126
  • OZCAN, E. and ONBASIOGLU, E., 2004. Genetic algorithms for parallel code optimization In: Evolutionary Computation, 2004. CEC2004. Congress on. 1375-1381
  • OZCAN, E. and ERENTURK, M., 2004. A brief review of memetic algorithms for solving Euclidean 2D traveling salesrep problem In: Proc. of the 13th Turkish Symposium on Artificial Intelligence and Neural Networks. 99-108
  • OZCAN, E. and HULAGU, B., 2004. A simple intelligent agent for playing abalone game: Abla In: Proceedings of the 13th Turkish Symposium on Artificial Intelligence and Neural Networks. 281-290,
  • ALKAN, A. and OZCAN, E., 2003. Memetic algorithms for timetabling In: Evolutionary Computation, 2003. CEC'03. The 2003 Congress on. 1796-1802
  • OZCAN, E. and ALKAN, A., 2002. Timetabling using a steady state genetic algorithm In: The 4th international conference on the Practice And Theory of Automated Timetabling.
  • OZCAN, E. and MOHAN, C.K., 1999. Particle swarm optimization: surfing the waves In: Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on.
  • OZCAN, E. and MOHAN, C.K., 1998. Analysis of a simple particle swarm optimization system In: Intelligent Engineering Systems Through Artificial Neural Networks. 253-258
  • OZCAN, E. and MOHAN, C., 1998. Steady state memetic algorithm for partial shape matching In: Evolutionary Programming VII. 527-536
  • OZCAN, E. and MOHAN, C.K., 1997. Partial shape matching using genetic algorithms Pattern Recognition Letters. 18(10), 987-992
  • OZCAN, E. and MOHAN, C.K., 1996. Shape recognition using genetic algorithms In: Evolutionary Computation, 1996., Proceedings of IEEE International Conference on. 411-416

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