TY - JOUR T1 - A user-friendly web portal for T-Coffee on supercomputers JF - BMC Bioinformatics Y1 - 2011 A1 - J. Rius A1 - F. Cores A1 - F. Solsona A1 - van Hemert, J. I. A1 - Koetsier, J. A1 - C. Notredame KW - e-Science KW - portal KW - rapid AB - Background Parallel T-Coffee (PTC) was the first parallel implementation of the T-Coffee multiple sequence alignment tool. It is based on MPI and RMA mechanisms. Its purpose is to reduce the execution time of the large-scale sequence alignments. It can be run on distributed memory clusters allowing users to align data sets consisting of hundreds of proteins within a reasonable time. However, most of the potential users of this tool are not familiar with the use of grids or supercomputers. Results In this paper we show how PTC can be easily deployed and controlled on a super computer architecture using a web portal developed using Rapid. Rapid is a tool for efficiently generating standardized portlets for a wide range of applications and the approach described here is generic enough to be applied to other applications, or to deploy PTC on different HPC environments. Conclusions The PTC portal allows users to upload a large number of sequences to be aligned by the parallel version of TC that cannot be aligned by a single machine due to memory and execution time constraints. The web portal provides a user-friendly solution. VL - 12 UR - http://www.biomedcentral.com/1471-2105/12/150 ER - TY - JOUR T1 - Correcting for intra-experiment variation in Illumina BeadChip data is necessary to generate robust gene-expression profiles JF - BMC Genomics Y1 - 2010 A1 - R. R. Kitchen A1 - V. S. Sabine A1 - A. H. Sims A1 - E. J. Macaskill A1 - L. Renshaw A1 - J. S. Thomas A1 - van Hemert, J. I. A1 - J. M. Dixon A1 - J. M. S. Bartlett AB - Background Microarray technology is a popular means of producing whole genome transcriptional profiles, however high cost and scarcity of mRNA has led many studies to be conducted based on the analysis of single samples. We exploit the design of the Illumina platform, specifically multiple arrays on each chip, to evaluate intra-experiment technical variation using repeated hybridisations of universal human reference RNA (UHRR) and duplicate hybridisations of primary breast tumour samples from a clinical study. Results A clear batch-specific bias was detected in the measured expressions of both the UHRR and clinical samples. This bias was found to persist following standard microarray normalisation techniques. However, when mean-centering or empirical Bayes batch-correction methods (ComBat) were applied to the data, inter-batch variation in the UHRR and clinical samples were greatly reduced. Correlation between replicate UHRR samples improved by two orders of magnitude following batch-correction using ComBat (ranging from 0.9833-0.9991 to 0.9997-0.9999) and increased the consistency of the gene-lists from the duplicate clinical samples, from 11.6% in quantile normalised data to 66.4% in batch-corrected data. The use of UHRR as an inter-batch calibrator provided a small additional benefit when used in conjunction with ComBat, further increasing the agreement between the two gene-lists, up to 74.1%. Conclusion In the interests of practicalities and cost, these results suggest that single samples can generate reliable data, but only after careful compensation for technical bias in the experiment. We recommend that investigators appreciate the propensity for such variation in the design stages of a microarray experiment and that the use of suitable correction methods become routine during the statistical analysis of the data. VL - 11 UR - http://www.biomedcentral.com/1471-2164/11/134 IS - 134 ER - TY - JOUR T1 - The Circulate Architecture: Avoiding Workflow Bottlenecks Caused By Centralised Orchestration JF - Cluster Computing Y1 - 2009 A1 - Barker, A. A1 - Weissman, J. A1 - van Hemert, J. I. KW - grid computing KW - workflow VL - 12 UR - http://www.springerlink.com/content/080q5857711w2054/?p=824749739c6a432ea95a0c3b59f4025f&pi=1 ER - TY - CHAP T1 - Exploiting Fruitful Regions in Dynamic Routing using Evolutionary Computation T2 - Studies in Computational Intelligence Y1 - 2009 A1 - van Hemert, J. I. A1 - la Poutré, J. A. ED - Pereira Babtista, F. ED - Tavares, J. JF - Studies in Computational Intelligence PB - Springer VL - 161 SN - 978-3-540-85151-6 N1 - Awaiting publication (due October 2008) ER - TY - JOUR T1 - Giving Computational Science a Friendly Face JF - Zero-In Y1 - 2009 A1 - van Hemert, J. I. A1 - Koetsier, J. AB - Today, most researchers from any discipline will successfully use web-based e-commerce systems to book flights to attend their conferences. But when these same researchers are confronted with compute-intensive problems, they cannot expect elaborate web-based systems to enable their domain-specific tasks. VL - 1 UR - http://www.beliefproject.org/zero-in/zero-in-third-edition/zero-in-issue-3 IS - 3 ER - TY - CONF T1 - Portals for Life Sciences—a Brief Introduction T2 - Proceedings of the IWPLS09 International Workshop on Portals for Life Sciences Y1 - 2009 A1 - Gesing, Sandra A1 - Kohlbacher, O. A1 - van Hemert, J. I. AB - The topic ”‘Portals for Life Sciences”’ includes various research fields, on the one hand many different topics out of life sciences, e.g. mass spectrometry, on the other hand portal technologies and different aspects of computer science, such as usability of user interfaces and security of systems. The main aspect about portals is to simplify the user’s interaction with computational resources which are concer- ted to a supported application domain. JF - Proceedings of the IWPLS09 International Workshop on Portals for Life Sciences T3 - CEUR Workshop Proceedings UR - http://ceur-ws.org/Vol-513/paper01.pdf ER - TY - CONF T1 - Rapid chemistry portals through engaging researchers T2 - Fifth IEEE International Conference on e-Science Y1 - 2009 A1 - Koetsier, J. A1 - Turner, A. A1 - Richardson, P. A1 - van Hemert, J. I. ED - Trefethen, A ED - De Roure, D AB - In this study, we apply a methodology for rapid development of portlets for scientific computing to the domain of computational chemistry. We report results in terms of the portals delivered, the changes made to our methodology and the experience gained in terms of interaction with domain-specialists. Our major contributions are: several web portals for teaching and research in computational chemistry; a successful transition to having our development tool used by the domain specialist as opposed by us, the developers; and an updated version of our methodology and technology for rapid development of portlets for computational science, which is free for anyone to pick up and use. JF - Fifth IEEE International Conference on e-Science CY - Oxford, UK ER - TY - CONF T1 - Rapid development of computational science portals T2 - Proceedings of the IWPLS09 International Workshop on Portals for Life Sciences Y1 - 2009 A1 - Koetsier, J. A1 - van Hemert, J. I. ED - Gesing, S. ED - van Hemert, J. I. KW - portal JF - Proceedings of the IWPLS09 International Workshop on Portals for Life Sciences T3 - CEUR Workshop Proceedings PB - e-Science Institute CY - Edinburgh UR - http://ceur-ws.org/Vol-513/paper05.pdf ER - TY - JOUR T1 - Towards a Virtual Fly Brain JF - Philosophical Transactions A Y1 - 2009 A1 - Armstrong, J. D. A1 - van Hemert, J. I. KW - e-Science AB - Models of the brain that simulate sensory input, behavioural output and information processing in a biologically plausible manner pose significant challenges to both Computer Science and Biology. Here we investigated strategies that could be used to create a model of the insect brain, specifically that of Drosophila melanogaster which is very widely used in laboratory research. The scale of the problem is an order of magnitude above the most complex of the current simulation projects and it is further constrained by the relative sparsity of available electrophysiological recordings from the fly nervous system. However, fly brain research at the anatomical and behavioural level offers some interesting opportunities that could be exploited to create a functional simulation. We propose to exploit these strengths of Drosophila CNS research to focus on a functional model that maps biologically plausible network architecture onto phenotypic data from neuronal inhibition and stimulation studies, leaving aside biophysical modelling of individual neuronal activity for future models until more data is available. VL - 367 UR - http://rsta.royalsocietypublishing.org/content/367/1896/2387.abstract ER - TY - JOUR T1 - Using the DCC Lifecycle Model to Curate a Gene Expression Database: A Case Study JF - International Journal of Digital Curation Y1 - 2009 A1 - O’Donoghue, J. A1 - van Hemert, J. I. AB - Developmental Gene Expression Map (DGEMap) is an EU-funded Design Study, which will accelerate an integrated European approach to gene expression in early human development. As part of this design study, we have had to address the challenges and issues raised by the long-term curation of such a resource. As this project is primarily one of data creators, learning about curation, we have been looking at some of the models and tools that are already available in the digital curation field in order to inform our thinking on how we should proceed with curating DGEMap. This has led us to uncover a wide range of resources for data creators and curators alike. Here we will discuss the future curation of DGEMap as a case study. We believe our experience could be instructive to other projects looking to improve the curation and management of their data. PB - UKOLN VL - 4 UR - http://www.ijdc.net/index.php/ijdc/article/view/134 IS - 3 ER - TY - CHAP T1 - Contraction-Based Heuristics to Improve the Efficiency of Algorithms Solving the Graph Colouring Problem T2 - Studies in Computational Intelligence Y1 - 2008 A1 - Juhos, I. A1 - van Hemert, J. I. ED - Cotta, C. ED - van Hemert, J. I. KW - constraint satisfaction KW - evolutionary computation KW - graph colouring JF - Studies in Computational Intelligence PB - Springer ER - TY - CONF T1 - Matching Spatial Regions with Combinations of Interacting Gene Expression Patterns T2 - Communications in Computer and Information Science Y1 - 2008 A1 - van Hemert, J. I. A1 - Baldock, R. A. ED - M. Elloumi ED - \emph ED - et al KW - biomedical KW - data mining KW - DGEMap KW - e-Science AB - The Edinburgh Mouse Atlas aims to capture in-situ gene expression patterns in a common spatial framework. In this study, we construct a grammar to define spatial regions by combinations of these patterns. Combinations are formed by applying operators to curated gene expression patterns from the atlas, thereby resembling gene interactions in a spatial context. The space of combinations is searched using an evolutionary algorithm with the objective of finding the best match to a given target pattern. We evaluate the method by testing its robustness and the statistical significance of the results it finds. JF - Communications in Computer and Information Science PB - Springer Verlag ER - TY - CONF T1 - Mining spatial gene expression data for association rules T2 - Lecture Notes in Bioinformatics Y1 - 2007 A1 - van Hemert, J. I. A1 - Baldock, R. A. ED - S. Hochreiter ED - R. Wagner KW - biomedical KW - data mining KW - DGEMap KW - e-Science AB - We analyse data from the Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) which is a high quality data source for spatio-temporal gene expression patterns. Using a novel process whereby generated patterns are used to probe spatially-mapped gene expression domains, we are able to get unbiased results as opposed to using annotations based predefined anatomy regions. We describe two processes to form association rules based on spatial configurations, one that associates spatial regions, the other associates genes. JF - Lecture Notes in Bioinformatics PB - Springer Verlag UR - http://dx.doi.org/10.1007/978-3-540-71233-6_6 ER - TY - JOUR T1 - Evolving combinatorial problem instances that are difficult to solve JF - Evolutionary Computation Y1 - 2006 A1 - van Hemert, J. I. KW - constraint programming KW - constraint satisfaction KW - evolutionary computation KW - problem evolving KW - satisfiability KW - travelling salesman AB - In this paper we demonstrate how evolutionary computation can be used to acquire difficult to solve combinatorial problem instances, thereby stress-testing the corresponding algorithms used to solve these instances. The technique is applied in three important domains of combinatorial optimisation, binary constraint satisfaction, Boolean satisfiability, and the travelling salesman problem. Problem instances acquired through this technique are more difficult than ones found in popular benchmarks. We analyse these evolved instances with the aim to explain their difficulty in terms of structural properties, thereby exposing the weaknesses of corresponding algorithms. VL - 14 UR - http://www.mitpressjournals.org/toc/evco/14/4 ER - TY - CONF T1 - Improving Graph Colouring Algorithms and Heuristics Using a Novel Representation T2 - Springer Lecture Notes on Computer Science Y1 - 2006 A1 - Juhos, I. A1 - van Hemert, J. I. ED - J. Gottlieb ED - G. Raidl KW - constraint satisfaction KW - graph colouring AB - We introduce a novel representation for the graph colouring problem, called the Integer Merge Model, which aims to reduce the time complexity of an algorithm. Moreover, our model provides useful information for guiding heuristics as well as a compact description for algorithms. To verify the potential of the model, we use it in dsatur, in an evolutionary algorithm, and in the same evolutionary algorithm extended with heuristics. An empiricial investigation is performed to show an increase in efficiency on two problem suites , a set of practical problem instances and a set of hard problem instances from the phase transition. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag ER - TY - JOUR T1 - Increasing the efficiency of graph colouring algorithms with a representation based on vector operations JF - Journal of Software Y1 - 2006 A1 - Juhos, I. A1 - van Hemert, J. I. KW - graph colouring AB - We introduce a novel representation for the graph colouring problem, called the Integer Merge Model, which aims to reduce the time complexity of graph colouring algorithms. Moreover, this model provides useful information to aid in the creation of heuristics that can make the colouring process even faster. It also serves as a compact definition for the description of graph colouring algorithms. To verify the potential of the model, we use it in the complete algorithm DSATUR, and in two version of an incomplete approximation algorithm; an evolutionary algorithm and the same evolutionary algorithm extended with guiding heuristics. Both theoretical and empirical results are provided investigation is performed to show an increase in the efficiency of solving graph colouring problems. Two problem suites were used for the empirical evidence: a set of practical problem instances and a set of hard problem instances from the phase transition. VL - 1 ER - TY - CONF T1 - Neighborhood Searches for the Bounded Diameter Minimum Spanning Tree Problem Embedded in a VNS, EA, and ACO T2 - Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2006) Y1 - 2006 A1 - Gruber, M. A1 - van Hemert, J. I. A1 - Raidl, G. R. ED - Maarten Keijzer ED - et al KW - constraint satisfaction KW - evolutionary computation KW - variable neighbourhood search AB - We consider the Bounded Diameter Minimum Spanning Tree problem and describe four neighbourhood searches for it. They are used as local improvement strategies within a variable neighbourhood search (VNS), an evolutionary algorithm (EA) utilising a new encoding of solutions, and an ant colony optimisation (ACO).We compare the performance in terms of effectiveness between these three hybrid methods on a suite f popular benchmark instances, which contains instances too large to solve by current exact methods. Our results show that the EA and the ACO outperform the VNS on almost all used benchmark instances. Furthermore, the ACO yields most of the time better solutions than the EA in long-term runs, whereas the EA dominates when the computation time is strongly restricted. JF - Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2006) PB - ACM CY - Seattle, USA VL - 2 ER - TY - CONF T1 - Complexity Transitions in Evolutionary Algorithms: Evaluating the impact of the initial population T2 - Proceedings of the Congress on Evolutionary Computation Y1 - 2005 A1 - Defaweux, A. A1 - Lenaerts, T. A1 - van Hemert, J. I. A1 - Parent, J. KW - constraint satisfaction KW - transition models AB - This paper proposes an evolutionary approach for the composition of solutions in an incremental way. The approach is based on the metaphor of transitions in complexity discussed in the context of evolutionary biology. Partially defined solutions interact and evolve into aggregations until a full solution for the problem at hand is found. The impact of the initial population on the outcome and the dynamics of the process is evaluated using the domain of binary constraint satisfaction problems. JF - Proceedings of the Congress on Evolutionary Computation PB - {IEEE} Press ER - TY - CONF T1 - Evolutionary Transitions as a Metaphor for Evolutionary Optimization T2 - LNAI 3630 Y1 - 2005 A1 - Defaweux, A. A1 - Lenaerts, T. A1 - van Hemert, J. I. ED - M. Capcarrere ED - A. A. Freitas ED - P. J. Bentley ED - C. G. Johnson ED - J. Timmis KW - constraint satisfaction KW - transition models AB - This paper proposes a computational model for solving optimisation problems that mimics the principle of evolutionary transitions in individual complexity. More specifically it incorporates mechanisms for the emergence of increasingly complex individuals from the interaction of more simple ones. The biological principles for transition are outlined and mapped onto an evolutionary computation context. The class of binary constraint satisfaction problems is used to illustrate the transition mechanism. JF - LNAI 3630 PB - Springer-Verlag SN - 3-540-28848-1 ER - TY - CONF T1 - Heuristic Colour Assignment Strategies for Merge Models in Graph Colouring T2 - Springer Lecture Notes on Computer Science Y1 - 2005 A1 - Juhos, I. A1 - Tóth, A. A1 - van Hemert, J. I. ED - G. Raidl ED - J. Gottlieb KW - constraint satisfaction KW - graph colouring AB - In this paper, we combine a powerful representation for graph colouring problems with different heuristic strategies for colour assignment. Our novel strategies employ heuristics that exploit information about the partial colouring in an aim to improve performance. An evolutionary algorithm is used to drive the search. We compare the different strategies to each other on several very hard benchmarks and on generated problem instances, and show where the novel strategies improve the efficiency. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin ER - TY - CONF T1 - Property analysis of symmetric travelling salesman problem instances acquired through evolution T2 - Springer Lecture Notes on Computer Science Y1 - 2005 A1 - van Hemert, J. I. ED - G. Raidl ED - J. Gottlieb KW - problem evolving KW - travelling salesman AB - We show how an evolutionary algorithm can successfully be used to evolve a set of difficult to solve symmetric travelling salesman problem instances for two variants of the Lin-Kernighan algorithm. Then we analyse the instances in those sets to guide us towards deferring general knowledge about the efficiency of the two variants in relation to structural properties of the symmetric travelling salesman problem. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin ER - TY - CONF T1 - Transition Models as an incremental approach for problem solving in Evolutionary Algorithms T2 - Proceedings of the Genetic and Evolutionary Computation Conference Y1 - 2005 A1 - Defaweux, A. A1 - Lenaerts, T. A1 - van Hemert, J. I. A1 - Parent, J. ED - H.-G. Beyer ED - et al KW - constraint satisfaction KW - transition models AB - This paper proposes an incremental approach for building solutions using evolutionary computation. It presents a simple evolutionary model called a Transition model. It lets building units of a solution interact and then uses an evolutionary process to merge these units toward a full solution for the problem at hand. The paper provides a preliminary study on the evolutionary dynamics of this model as well as an empirical comparison with other evolutionary techniques on binary constraint satisfaction. JF - Proceedings of the Genetic and Evolutionary Computation Conference PB - {ACM} Press ER - TY - CONF T1 - Binary Merge Model Representation of the Graph Colouring Problem T2 - Springer Lecture Notes on Computer Science Y1 - 2004 A1 - Juhos, I. A1 - Tóth, A. A1 - van Hemert, J. I. ED - J. Gottlieb ED - G. Raidl KW - constraint satisfaction KW - graph colouring AB - This paper describes a novel representation and ordering model that aided by an evolutionary algorithm, is used in solving the graph \emph{k}-colouring problem. Its strength lies in reducing the search space by breaking symmetry. An empirical comparison is made with two other algorithms on a standard suit of problem instances and on a suit of instances in the phase transition where it shows promising results. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin SN - 3-540-21367-8 ER - TY - CONF T1 - Dynamic Routing Problems with Fruitful Regions: Models and Evolutionary Computation T2 - LNCS Y1 - 2004 A1 - van Hemert, J. I. A1 - la Poutré, J. A. ED - Xin Yao ED - Edmund Burke ED - Jose A. Lozano ED - Jim Smith ED - Juan J. Merelo-Guerv\'os ED - John A. Bullinaria ED - Jonathan Rowe ED - Peter Ti\v{n}o Ata Kab\'an ED - Hans-Paul Schwefel KW - dynamic problems KW - evolutionary computation KW - vehicle routing AB - We introduce the concept of fruitful regions in a dynamic routing context: regions that have a high potential of generating loads to be transported. The objective is to maximise the number of loads transported, while keeping to capacity and time constraints. Loads arrive while the problem is being solved, which makes it a real-time routing problem. The solver is a self-adaptive evolutionary algorithm that ensures feasible solutions at all times. We investigate under what conditions the exploration of fruitful regions improves the effectiveness of the evolutionary algorithm. JF - LNCS PB - Springer-Verlag CY - Birmingham, UK VL - 3242 SN - 3-540-23092-0 ER - TY - CONF T1 - Phase transition properties of clustered travelling salesman problem instances generated with evolutionary computation T2 - LNCS Y1 - 2004 A1 - van Hemert, J. I. A1 - Urquhart, N. B. ED - Xin Yao ED - Edmund Burke ED - Jose A. Lozano ED - Jim Smith ED - Juan J. Merelo-Guerv\'os ED - John A. Bullinaria ED - Jonathan Rowe ED - Peter Ti\v{n}o Ata Kab\'an ED - Hans-Paul Schwefel KW - evolutionary computation KW - problem evolving KW - travelling salesman AB - This paper introduces a generator that creates problem instances for the Euclidean symmetric travelling salesman problem. To fit real world problems, we look at maps consisting of clustered nodes. Uniform random sampling methods do not result in maps where the nodes are spread out to form identifiable clusters. To improve upon this, we propose an evolutionary algorithm that uses the layout of nodes on a map as its genotype. By optimising the spread until a set of constraints is satisfied, we are able to produce better clustered maps, in a more robust way. When varying the number of clusters in these maps and, when solving the Euclidean symmetric travelling salesman person using Chained Lin-Kernighan, we observe a phase transition in the form of an easy-hard-easy pattern. JF - LNCS PB - Springer-Verlag CY - Birmingham, UK VL - 3242 SN - 3-540-23092-0 UR - http://www.vanhemert.co.uk/files/clustered-phase-transition-tsp.tar.gz ER - TY - JOUR T1 - Robust parameter settings for variation operators by measuring the resampling ratio: A study on binary constraint satisfaction problems JF - Journal of Heuristics Y1 - 2004 A1 - van Hemert, J. I. A1 - Bäck, T. KW - constraint satisfaction KW - evolutionary computation KW - resampling ratio AB - In this article, we try to provide insight into the consequence of mutation and crossover rates when solving binary constraint satisfaction problems. This insight is based on a measurement of the space searched by an evolutionary algorithm. From data empirically acquired we describe the relation between the success ratio and the searched space. This is achieved using the resampling ratio, which is a measure for the amount of points revisited by a search algorithm. This relation is based on combinations of parameter settings for the variation operators. We then show that the resampling ratio is useful for identifying the quality of parameter settings, and provide a range that corresponds to robust parameter settings. VL - 10 ER - TY - CONF T1 - A Study into Ant Colony Optimization, Evolutionary Computation and Constraint Programming on Binary Constraint Satisfaction Problems T2 - Springer Lecture Notes on Computer Science Y1 - 2004 A1 - van Hemert, J. I. A1 - Solnon, C. ED - J. Gottlieb ED - G. Raidl KW - ant colony optimisation KW - constraint programming KW - constraint satisfaction KW - evolutionary computation AB - We compare two heuristic approaches, evolutionary computation and ant colony optimisation, and a complete tree-search approach, constraint programming, for solving binary constraint satisfaction problems. We experimentally show that, if evolutionary computation is far from being able to compete with the two other approaches, ant colony optimisation nearly always succeeds in finding a solution, so that it can actually compete with constraint programming. The resampling ratio is used to provide insight into heuristic algorithms performances. Regarding efficiency, we show that if constraint programming is the fastest when instances have a low number of variables, ant colony optimisation becomes faster when increasing the number of variables. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin SN - 3-540-21367-8 ER - TY - JOUR T1 - Comparing Evolutionary Algorithms on Binary Constraint Satisfaction Problems JF - IEEE Transactions on Evolutionary Computation Y1 - 2003 A1 - Craenen, B. G. W. A1 - Eiben, A. E. A1 - van Hemert, J. I. KW - constraint satisfaction AB - Constraint handling is not straightforward in evolutionary algorithms (EA) since the usual search operators, mutation and recombination, are `blind' to constraints. Nevertheless, the issue is highly relevant, for many challenging problems involve constraints. Over the last decade numerous EAs for solving constraint satisfaction problems (CSP) have been introduced and studied on various problems. The diversity of approaches and the variety of problems used to study the resulting algorithms prevents a fair and accurate comparison of these algorithms. This paper aligns related work by presenting a concise overview and an extensive performance comparison of all these EAs on a systematically generated test suite of random binary CSPs. The random problem instance generator is based on a theoretical model that fixes deficiencies of models and respective generators that have been formerly used in the Evolutionary Computing (EC) field. VL - 7 UR - http://ieeexplore.ieee.org/xpl/abs_free.jsp?isNumber=27734&prod=JNL&arnumber=1237162&arSt=+424&ared=+444&arAuthor=+Craenen%2C+B.G.W.%3B++Eiben%2C+A.E.%3B++van+Hemert%2C+J.I.&arNumber=1237162&a_id0=1237161&a_id1=1237162&a_id2=1237163&a_id3=1237164&a_id4=12 ER - TY - CONF T1 - Evolving binary constraint satisfaction problem instances that are difficult to solve T2 - Proceedings of the IEEE 2003 Congress on Evolutionary Computation Y1 - 2003 A1 - van Hemert, J. I. KW - constraint satisfaction KW - problem evolving AB - We present a study on the difficulty of solving binary constraint satisfaction problems where an evolutionary algorithm is used to explore the space of problem instances. By directly altering the structure of problem instances and by evaluating the effort it takes to solve them using a complete algorithm we show that the evolutionary algorithm is able to detect problem instances that are harder to solve than those produced with conventional methods. Results from the search of the evolutionary algorithm confirm conjectures about where the most difficult to solve problem instances can be found with respect to the tightness. JF - Proceedings of the IEEE 2003 Congress on Evolutionary Computation PB - IEEE Press SN - 0-7803-7804-0 ER - TY - CONF T1 - A new permutation model for solving the graph k-coloring problem T2 - Kalmàr Workshop on Logic and Computer Science Y1 - 2003 A1 - Juhos, I. A1 - Tóth, A. A1 - Tezuka, M. A1 - Tann, P. A1 - van Hemert, J. I. KW - constraint satisfaction KW - graph colouring AB - This paper describes a novel representation and ordering model, that is aided by an evolutionary algorithm, is used in solving the graph k-coloring. A comparison is made between the new representation and an improved version of the traditional graph coloring technique DSATUR on an extensive list of graph k-coloring problem instances with different properties. The results show that our model outperforms the improved DSATUR on most of the problem instances. JF - Kalmàr Workshop on Logic and Computer Science ER - TY - CONF T1 - Comparing Classical Methods for Solving Binary Constraint Satisfaction Problems with State of the Art Evolutionary Computation T2 - Springer Lecture Notes on Computer Science Y1 - 2002 A1 - van Hemert, J. I. ED - S. Cagnoni ED - J. Gottlieb ED - E. Hart ED - M. Middendorf ED - G. Raidl KW - constraint satisfaction AB - Constraint Satisfaction Problems form a class of problems that are generally computationally difficult and have been addressed with many complete and heuristic algorithms. We present two complete algorithms, as well as two evolutionary algorithms, and compare them on randomly generated instances of binary constraint satisfaction prob-lems. We find that the evolutionary algorithms are less effective than the classical techniques. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin ER - TY - CONF T1 - Measuring the Searched Space to Guide Efficiency: The Principle and Evidence on Constraint Satisfaction T2 - Springer Lecture Notes on Computer Science Y1 - 2002 A1 - van Hemert, J. I. A1 - Bäck, T. ED - J. J. Merelo ED - A. Panagiotis ED - H.-G. Beyer ED - Jos{\'e}-Luis Fern{\'a}ndez-Villaca{\~n}as ED - Hans-Paul Schwefel KW - constraint satisfaction KW - resampling ratio AB - In this paper we present a new tool to measure the efficiency of evolutionary algorithms by storing the whole searched space of a run, a process whereby we gain insight into the number of distinct points in the state space an algorithm has visited as opposed to the number of function evaluations done within the run. This investigation demonstrates a certain inefficiency of the classical mutation operator with mutation-rate 1/l, where l is the dimension of the state space. Furthermore we present a model for predicting this inefficiency and verify it empirically using the new tool on binary constraint satisfaction problems. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin SN - 3-540-44139-5 ER - TY - CONF T1 - Use of Evolutionary Algorithms for Telescope Scheduling T2 - Integrated Modeling of Telescopes Y1 - 2002 A1 - Grim, R. A1 - Jansen, M. L. M. A1 - Baan, A. A1 - van Hemert, J. I. A1 - de Wolf, H. ED - Torben Anderson KW - constraint satisfaction KW - scheduling AB - LOFAR, a new radio telescope, will be designed to observe with up to 8 independent beams, thus allowing several simultaneous observations. Scheduling of multiple observations parallel in time, each having their own constraints, requires a more intelligent and flexible scheduling function then operated before. In support of the LOFAR radio telescope project, and in co-operation with Leiden University, Fokker Space has started a study to investigate the suitability of the use of evolutionary algorithms applied to complex scheduling problems. After a positive familiarisation phase, we now examine the potential use of evolutionary algorithms via a demonstration project. Results of the familiarisation phase, and the first results of the demonstration project are presented in this paper. JF - Integrated Modeling of Telescopes PB - The International Society for Optical Engineering ({SPIE}) VL - 4757 ER - TY - CONF T1 - Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems T2 - Springer Lecture Notes on Computer Science Y1 - 2001 A1 - Eggermont, J. A1 - van Hemert, J. I. ED - J. Miller ED - Tomassini, M. ED - P. L. Lanzi ED - C. Ryan ED - A. G. B. Tettamanzi ED - W. B. Langdon KW - data mining AB - In this paper we continue our study on adaptive genetic pro-gramming. We use Stepwise Adaptation of Weights to boost performance of a genetic programming algorithm on simple symbolic regression problems. We measure the performance of a standard GP and two variants of SAW extensions on two different symbolic regression prob-lems from literature. Also, we propose a model for randomly generating polynomials which we then use to further test all three GP variants. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin SN - 9-783540-418993 ER - TY - CONF T1 - An Engineering Approach to Evolutionary Art T2 - Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001) Y1 - 2001 A1 - van Hemert, J. I. A1 - Jansen, M. L. M. ED - Lee Spector ED - Erik D. Goodman ED - Annie Wu ED - W. B. Langdon ED - Hans-Michael Voigt ED - Mitsuo Gen ED - Sandip Sen ED - Marco Dorigo ED - Shahram Pezeshk ED - Max H. Garzon ED - Edmund Burke KW - evolutionary art AB - We present a general system that evolves art on the Internet. The system runs on a server which enables it to collect information about its usage world wide; its core uses operators and representations from genetic program-ming. We show two types of art that can be evolved using this general system. JF - Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001) PB - Morgan Kaufmann Publishers, San Francisco ER - TY - CONF T1 - Evolutionary Computation in Constraint Satisfaction and Machine Learning --- An abstract of my PhD. T2 - Proceedings of the Brussels Evolutionary Algorithms Day (BEAD-2001) Y1 - 2001 A1 - van Hemert, J. I. ED - Anne Defaweux ED - Bernard Manderick ED - Tom Lenearts ED - Johan Parent ED - Piet van Remortel KW - constraint satisfaction KW - data mining JF - Proceedings of the Brussels Evolutionary Algorithms Day (BEAD-2001) PB - Vrije Universiteit Brussel (VUB) ER - TY - CONF T1 - A ``Futurist'' approach to dynamic environments T2 - Proceedings of the Workshops at the Genetic and Evolutionary Computation Conference, Dynamic Optimization Problems Y1 - 2001 A1 - van Hemert, J. I. A1 - Van Hoyweghen, C. A1 - Lukschandl, E. A1 - Verbeeck, K. ED - J. Branke ED - Th. B{\"a}ck KW - dynamic problems AB - The optimization of dynamic environments has proved to be a difficult area for Evolutionary Algorithms. As standard haploid populations find it difficult to track a moving target, diffKerent schemes have been suggested to improve the situation. We study a novel approach by making use of a meta learner which tries to predict the next state of the environment, i.e. the next value of the goal the individuals have to achieve, by making use of the accumulated knowledge from past performance. JF - Proceedings of the Workshops at the Genetic and Evolutionary Computation Conference, Dynamic Optimization Problems PB - Morgan Kaufmann Publishers, San Francisco ER - TY - CONF T1 - Constraint Satisfaction Problems and Evolutionary Algorithms: A Reality Check T2 - Proceedings of the Twelfth Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'00) Y1 - 2000 A1 - van Hemert, J. I. ED - van den Bosch, A. ED - H. Weigand KW - constraint satisfaction AB - Constraint satisfaction has been the subject of many studies. Different areas of research have tried to solve all kind of constraint problems. Here we will look at a general model for constraint satisfaction problems in the form of binary constraint satisfaction. The problems generated from this model are studied in the research area of constraint programming and in the research area of evolutionary computation. This paper provides an empirical comparison of two techniques from each area. Basically, this is a check on how well both areas are doing. It turns out that, although evolutionary algorithms are doing well, classic approaches are still more successful. JF - Proceedings of the Twelfth Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'00) PB - BNVKI, Dutch and the Belgian AI Association ER - TY - JOUR T1 - De Creatieve Computer JF - AIgg Kennisgeving Y1 - 2000 A1 - van Hemert, J. I. KW - evolutionary art AB - Here we show an application that generates images resembling art as it was produced by Mondriaan, a Dutch artist, well known for his minimalistic and pure abstract pieces of art. The current version generates images using a linear chromosome and a recursive function as a decoder. PB - Artifici{\"e}le Intelligentie gebruikers groep VL - 13 N1 - invited article (in Dutch) ER - TY - CONF T1 - Stepwise Adaptation of Weights for Symbolic Regression with Genetic Programming T2 - Proceedings of the Twelfth Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'00) Y1 - 2000 A1 - Eggermont, J. A1 - van Hemert, J. I. ED - van den Bosch, A. ED - H. Weigand KW - data mining KW - genetic programming AB - In this paper we continue study on the Stepwise Adaptation of Weights (SAW) technique. Previous studies on constraint satisfaction and data clas-sification have indicated that SAW is a promising technique to boost the performance of evolutionary algorithms. Here we use SAW to boost per-formance of a genetic programming algorithm on simple symbolic regression problems. We measure the performance of a standard GP and two variants of SAW extensions on two different symbolic regression problems. JF - Proceedings of the Twelfth Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'00) PB - BNVKI, Dutch and the Belgian AI Association ER - TY - CONF T1 - Adapting the Fitness Function in GP for Data Mining T2 - Springer Lecture Notes on Computer Science Y1 - 1999 A1 - Eggermont, J. A1 - Eiben, A. E. A1 - van Hemert, J. I. ED - R. Poli ED - P. Nordin ED - W. B. Langdon ED - T. C. Fogarty KW - data mining KW - genetic programming AB - In this paper we describe how the Stepwise Adaptation of Weights (SAW) technique can be applied in genetic programming. The SAW-ing mechanism has been originally developed for and successfully used in EAs for constraint satisfaction problems. Here we identify the very basic underlying ideas behind SAW-ing and point out how it can be used for different types of problems. In particular, SAW-ing is well suited for data mining tasks where the fitness of a candidate solution is composed by `local scores' on data records. We evaluate the power of the SAW-ing mechanism on a number of benchmark classification data sets. The results indicate that extending the GP with the SAW-ing feature increases its performance when different types of misclassifications are not weighted differently, but leads to worse results when they are. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin SN - 3-540-65899-8 ER - TY - CONF T1 - Comparing genetic programming variants for data classification T2 - Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'99) Y1 - 1999 A1 - Eggermont, J. A1 - Eiben, A. E. A1 - van Hemert, J. I. ED - E. Postma ED - M. Gyssens KW - classification KW - data mining KW - genetic programming AB - This article is a combined summary of two papers written by the authors. Binary data classification problems (with exactly two disjoint classes) form an important application area of machine learning techniques, in particular genetic programming (GP). In this study we compare a number of different variants of GP applied to such problems whereby we investigate the effect of two significant changes in a fixed GP setup in combination with two different evolutionary models JF - Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'99) PB - BNVKI, Dutch and the Belgian AI Association ER - TY - CONF T1 - A comparison of genetic programming variants for data classification T2 - Springer Lecture Notes on Computer Science Y1 - 1999 A1 - Eggermont, J. A1 - Eiben, A. E. A1 - van Hemert, J. I. ED - D. J. Hand ED - J. N. Kok ED - M. R. Berthold KW - classification KW - data mining KW - genetic programming AB - In this paper we report the results of a comparative study on different variations of genetic programming applied on binary data classification problems. The first genetic programming variant is weighting data records for calculating the classification error and modifying the weights during the run. Hereby the algorithm is defining its own fitness function in an on-line fashion giving higher weights to `hard' records. Another novel feature we study is the atomic representation, where `Booleanization' of data is not performed at the root, but at the leafs of the trees and only Boolean functions are used in the trees' body. As a third aspect we look at generational and steady-state models in combination of both features. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin SN - 3-540-66332-0 ER - TY - CONF T1 - Mondriaan Art by Evolution T2 - Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'99) Y1 - 1999 A1 - van Hemert, J. I. A1 - Eiben, A. E. ED - E. Postma ED - M. Gyssens KW - evolutionary art AB - Here we show an application that generates images resembling art as it was produced by Mondriaan, a Dutch artist, well known for his minimalistic and pure abstract pieces of art. The current version generates images using a linear chromosome and a recursive function as a decoder. JF - Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'99) PB - BNVKI, Dutch and the Belgian AI Association ER - TY - CONF T1 - Population dynamics and emerging features in AEGIS T2 - Proceedings of the Genetic and Evolutionary Computation Conference Y1 - 1999 A1 - Eiben, A. E. A1 - Elia, D. A1 - van Hemert, J. I. ED - W. Banzhaf ED - J. Daida ED - Eiben, A. E. ED - M. H. Garzon ED - V. Honavar ED - M. Jakiela ED - R. E. Smith KW - dynamic problems AB - We describe an empirical investigation within an artificial world, aegis, where a population of animals and plants is evolving. We compare different system setups in search of an `ideal' world that allows a constantly high number of inhabitants for a long period of time. We observe that high responsiveness at individual level (speed of movement) or population level (high fertility) are `ideal'. Furthermore, we investigate the emergence of the so-called mental features of animals determining their social, consumptional and aggressive behaviour. The tests show that being socially oriented is generally advantageous, while agressive behaviour only emerges under specific circumstances. JF - Proceedings of the Genetic and Evolutionary Computation Conference PB - Morgan Kaufmann Publishers, San Francisco ER - TY - CHAP T1 - SAW-ing EAs: adapting the fitness function for solving constrained problems T2 - New ideas in optimization Y1 - 1999 A1 - Eiben, A. E. A1 - van Hemert, J. I. ED - D. Corne ED - M. Dorigo ED - F. Glover KW - constraint satisfaction AB - In this chapter we describe a problem independent method for treating constrain ts in an evolutionary algorithm. Technically, this method amounts to changing the defini tion of the fitness function during a run of an EA, based on feedback from the search pr ocess. Obviously, redefining the fitness function means redefining the problem to be sol ved. On the short term this deceives the algorithm making the fitness values deteriorate , but as experiments clearly indicate, on the long run it is beneficial. We illustrate t he power of the method on different constraint satisfaction problems and point out other application areas of this technique. JF - New ideas in optimization PB - McGraw-Hill, London ER - TY - CONF T1 - Extended abstract: Solving Binary Constraint Satisfaction Problems using Evolutionary Algorithms with an Adaptive Fitness Function T2 - Proceedings of the Xth Netherlands/Belgium Conference on Artificial Intelligence (NAIC'98) Y1 - 1998 A1 - Eiben, A. E. A1 - van Hemert, J. I. A1 - Marchiori, E. A1 - Steenbeek, A. G. ED - la Poutré, J. A. ED - van den Herik, J. KW - constraint satisfaction JF - Proceedings of the Xth Netherlands/Belgium Conference on Artificial Intelligence (NAIC'98) PB - BNVKI, Dutch and the Belgian AI Association N1 - Abstract of \cite{EHMS98} ER - TY - JOUR T1 - Graph Coloring with Adaptive Evolutionary Algorithms JF - Journal of Heuristics Y1 - 1998 A1 - Eiben, A. E. A1 - van der Hauw, J. K. A1 - van Hemert, J. I. KW - constraint satisfaction KW - graph colouring AB - This paper presents the results of an experimental investigation on solving graph coloring problems with Evolutionary Algorithms (EA). After testing different algorithm variants we conclude that the best option is an asexual EA using order-based representation and an adaptation mechanism that periodically changes the fitness function during the evolution. This adaptive EA is general, using no domain specific knowledge, except, of course, from the decoder (fitness function). We compare this adaptive EA to a powerful traditional graph coloring technique DSatur and the Grouping GA on a wide range of problem instances with different size, topology and edge density. The results show that the adaptive EA is superior to the Grouping GA and outperforms DSatur on the hardest problem instances. Furthermore, it scales up better with the problem size than the other two algorithms and indicates a linear computational complexity. PB - Kluwer Academic Publishers VL - 4 ER - TY - CONF T1 - Solving Binary Constraint Satisfaction Problems using Evolutionary Algorithms with an Adaptive Fitness Function T2 - Springer Lecture Notes on Computer Science Y1 - 1998 A1 - Eiben, A. E. A1 - van Hemert, J. I. A1 - Marchiori, E. A1 - Steenbeek, A. G. ED - Eiben, A. E. ED - Th. B{\"a}ck ED - M. Schoenauer ED - H.-P. Schwefel KW - constraint satisfaction AB - This paper presents a comparative study of Evolutionary Algorithms (EAs) for Constraint Satisfaction Problems (CSPs). We focus on EAs where fitness is based on penalization of constraint violations and the penalties are adapted during the execution. Three different EAs based on this approach are implemented. For highly connected constraint networks, the results provide further empirical support to the theoretical prediction of the phase transition in binary CSPs. JF - Springer Lecture Notes on Computer Science PB - Springer-Verlag, Berlin ER -