TY - CHAP T1 - Evolutionary Computation and Constraint Satisfaction Y1 - 2015 A1 - van Hemert, J. ED - Kacpryk, J. ED - Pedrycz, W. KW - constraint satisfaction KW - evolutionary computation AB - In this chapter we will focus on the combination of evolutionary computation techniques and constraint satisfaction problems. Constraint Programming (CP) is another approach to deal with constraint satisfaction problems. In fact, it is an important prelude to the work covered here as it advocates itself as an alternative approach to programming (Apt). The first step is to formulate a problem as a CSP such that techniques from CP, EC, combinations of the two (c.f., Hybrid) or other approaches can be deployed to solve the problem. The formulation of a problem has an impact on its complexity in terms of effort required to either find a solution or proof no solution exists. It is therefore vital to spend time on getting this right. Main differences between CP and EC. CP defines search as iterative steps over a search tree where nodes are partial solutions to the problem where not all variables are assigned values. The search then maintain a partial solution that satisfies all variables assigned values. Instead, in EC most often solver sample a space of candidate solutions where variables are all assigned values. None of these candidate solutions will satisfy all constraints in the problem until a solution is found. Another major difference is that many constraint solvers from CP are sound whereas EC solvers are not. A solver is sound if it always finds a solution if it exists. PB - Springer ER - TY - JOUR T1 - Embedded systems for global e-Social Science: Moving computation rather than data JF - Future Generation Computer Systems Y1 - 2013 A1 - Ashley D. Lloyd A1 - Terence M. Sloan A1 - Antonioletti, Mario A1 - Gary McGilvary AB - There is a wealth of digital data currently being gathered by commercial and private concerns that could supplement academic research. To unlock this data it is important to gain the trust of the companies that hold the data as well as showing them how they may benefit from this research. Part of this trust is gained through established reputation and the other through the technology used to safeguard the data. This paper discusses how different technology frameworks have been applied to safeguard the data and facilitate collaborative work between commercial concerns and academic institutions. The paper focuses on the distinctive requirements of e-Social Science: access to large-scale data on behaviour in society in environments that impose confidentiality constraints on access. These constraints arise from both privacy concerns and the commercial sensitivities of that data. In particular, the paper draws on the experiences of building an intercontinental Grid–INWA–from its first operation connecting Australia and Scotland to its subsequent extension to China across the Trans-Eurasia Information Network–the first large-scale research and education network for the Asia-Pacific region. This allowed commercial data to be analysed by experts that were geographically distributed across the globe. It also provided an entry point for a major Chinese commercial organization to approve use of a Grid solution in a new collaboration provided the centre of gravity of the data is retained within the jurisdiction of the data owner. We describe why, despite this approval, an embedded solution was eventually adopted. We find that ‘data sovereignty’ dominates any decision on whether and how to participate in e-Social Science collaborations and how this might impact on a Cloud based solution to this type of collaboration. VL - 29 UR - http://www.sciencedirect.com/science/article/pii/S0167739X12002336 IS - 5 ER - TY - JOUR T1 - Exploiting Parallel R in the Cloud with SPRINT JF - Methods of Information in Medicine Y1 - 2013 A1 - Piotrowski, Michal A1 - Gary McGilvary A1 - Sloan, Terence A1 - Mewissen, Muriel A1 - Ashley Lloyd A1 - Forster, Thorsten A1 - Mitchell, Lawrence A1 - Ghazal, Peter A1 - Hill, Jon AB - Background: Advances in DNA Microarray devices and next-generation massively parallel DNA sequencing platforms have led to an exponential growth in data availability but the arising opportunities require adequate computing resources. High Performance Computing (HPC) in the Cloud offers an affordable way of meeting this need. Objectives: Bioconductor, a popular tool for high-throughput genomic data analysis, is distributed as add-on modules for the R statistical programming language but R has no native capabilities for exploiting multi-processor architectures. SPRINT is an R package that enables easy access to HPC for genomics researchers. This paper investigates: setting up and running SPRINT-enabled genomic analyses on Amazon’s Elastic Compute Cloud (EC2), the advantages of submitting applications to EC2 from different parts of the world and, if resource underutilization can improve application performance. Methods: The SPRINT parallel implementations of correlation, permutation testing, partitioning around medoids and the multi-purpose papply have been benchmarked on data sets of various size on Amazon EC2. Jobs have been submitted from both the UK and Thailand to investigate monetary differences. Results: It is possible to obtain good, scalable performance but the level of improvement is dependent upon the nature of algorithm. Resource underutilization can further improve the time to result. End-user’s location impacts on costs due to factors such as local taxation. Conclusions: Although not designed to satisfy HPC requirements, Amazon EC2 and cloud computing in general provides an interesting alternative and provides new possibilities for smaller organisations with limited funds. VL - 52 IS - 1 ER - TY - JOUR T1 - EnzML: multi-label prediction of enzyme classes using InterPro signatures. JF - BMC Bioinformatics Y1 - 2012 A1 - De Ferrari, Luna A1 - Stuart Aitken A1 - van Hemert, Jano A1 - Goryanin, Igor AB - BACKGROUND: Manual annotation of enzymatic functions cannot keep up with automatic genome sequencing. In this work we explore the capacity of InterPro sequence signatures to automatically predict enzymatic function. RESULTS: We present EnzML, a multi-label classification method that can efficiently account also for proteins with multiple enzymatic functions: 50,000 in UniProt. EnzML was evaluated using a standard set of 300,747 proteins for which the manually curated Swiss-Prot and KEGG databases have agreeing Enzyme Commission (EC) annotations. EnzML achieved more than 98% subset accuracy (exact match of all correct Enzyme Commission classes of a protein) for the entire dataset and between 87 and 97% subset accuracy in reannotating eight entire proteomes: human, mouse, rat, mouse-ear cress, fruit fly, the S. pombe yeast, the E. coli bacterium and the M. jannaschii archaebacterium. To understand the role played by the dataset size, we compared the cross-evaluation results of smaller datasets, either constructed at random or from specific taxonomic domains such as archaea, bacteria, fungi, invertebrates, plants and vertebrates. The results were confirmed even when the redundancy in the dataset was reduced using UniRef100, UniRef90 or UniRef50 clusters. CONCLUSIONS: InterPro signatures are a compact and powerful attribute space for the prediction of enzymatic function. This representation makes multi-label machine learning feasible in reasonable time (30 minutes to train on 300,747 instances with 10,852 attributes and 2,201 class values) using the Mulan Binary Relevance Nearest Neighbours algorithm implementation (BR-kNN). VL - 13 ER - TY - RPRT T1 - EDIM1 Progress Report Y1 - 2011 A1 - Paul Martin A1 - Malcolm Atkinson A1 - Parsons, Mark A1 - Adam Carter A1 - Gareth Francis AB - The Edinburgh Data-Intensive Machine (EDIM1) is the product of a joint collaboration between the data-intensive group at the School of Informatics and EPCC. EDIM1 is an experimental system, offering an alternative architecture for data-intensive computation and providing a platform for evaluating tools for data-intensive research; a 120 node cluster of ‘data-bricks’ with high storage yet modest computational capacity. This document gives some background into the context in which EDIM1 was designed and constructed, as well as providing an overview of its use so far and future plans. ER - TY - JOUR T1 - An evaluation of ontology matching in geo-service applications JF - Geoinformatica Y1 - 2011 A1 - Lorenzino Vaccari A1 - Pavel Shvaiko A1 - Juan Pane A1 - Paolo Besana A1 - Maurizio Marchese ER - TY - CHAP T1 - Exploiting P2P and Grid Computing Technologies for Resource Sharing to support High Performance Distributed System T2 - Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies and Applications Y1 - 2010 A1 - Liangxiu Han ED - Nick Antonopoulos ED - Georgios Exarchakos ED - Maozhen Li ED - Antonio Liottac JF - Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies and Applications PB - IGI Global publishing VL - 1 ER - TY - RPRT T1 - An e-Infrastructure for Collaborative Research in Human Embryo Development Y1 - 2009 A1 - Barker, Adam A1 - van Hemert, Jano I. A1 - Baldock, Richard A. A1 - Atkinson, Malcolm P. AB - Within the context of the EU Design Study Developmental Gene Expression Map, we identify a set of challenges when facilitating collaborative research on early human embryo development. These challenges bring forth requirements, for which we have identified solutions and technology. We summarise our solutions and demonstrate how they integrate to form an e-infrastructure to support collaborative research in this area of developmental biology. UR - http://arxiv.org/pdf/0901.2310v1 ER - TY - CONF T1 - An E-infrastructure to Support Collaborative Embryo Research T2 - Cluster Computing and the Grid Y1 - 2009 A1 - Barker, Adam A1 - van Hemert, Jano I. A1 - Baldock, Richard A. A1 - Atkinson, Malcolm P. JF - Cluster Computing and the Grid PB - IEEE Computer Society SN - 978-0-7695-3622-4 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 - RPRT T1 - Education and Training Task Force Report Y1 - 2008 A1 - Atkinson, M. A1 - Vander Meer, E. A1 - Fergusson, D. A1 - Artacho, M. AB - The development of e-Infrastructure, of which grid computing is a fundamental element, will have major economic and social benefits. Online and financial businesses already successfully use grid computing technologies, for instance. There are already demonstrations showing the benefits to engineering, medicine and the creative industries as well. New research methods and technologies generate large data sets that need to be shared in order to ensure continued social and scientific research and innovation. e-Infrastructure provides an environment for coping with these large data sets and for sharing data across regions. An investment in educating people in this technology, then, is an investment that will strengthen our economies and societies. In order to deliver e-Infrastructure education and training successfully in the EU, we must develop a policy framework that will ensure shared responsibility and equivalent training in the field. This document focuses primarily on the current state of grid and e-Science education, introducing key challenges and the opportunities available to educational planners that serve as a starting point for further work. It then proposes strategies and policies to provide a supportive framework for e-Infrastructure education and training. The ETTF Report concludes with policy recommendations to be taken forward by the e-IRG. These recommendations address issues such as the level of Member State investment in e-Infrastructure education, the harmonisation of education in distributed-computation thinking and in the use of e-Infrastructure and the development of standards for student and teacher identification, for the sharing of t-Infrastructure (and training material) and for accreditation. JF - e-Infrastructure Reflection Group UR - http://www.e-irg.eu/index.php?option=com_content&task=view&id=38&Itemid=37 ER - TY - CONF T1 - Eliminating the Middle Man: Peer-to-Peer Dataflow T2 - HPDC '08: Proceedings of the 17th International Symposium on High Performance Distributed Computing Y1 - 2008 A1 - Barker, Adam A1 - Weissman, Jon B. A1 - van Hemert, Jano KW - grid computing KW - workflow JF - HPDC '08: Proceedings of the 17th International Symposium on High Performance Distributed Computing PB - ACM ER - TY - Generic T1 - European Graduate Student Workshop on Evolutionary Computation Y1 - 2008 A1 - Di Chio, Cecilia A1 - Giacobini, Mario A1 - van Hemert, Jano ED - Di Chio, Cecilia ED - Giacobini, Mario ED - van Hemert, Jano KW - evolutionary computation AB - Evolutionary computation involves the study of problem-solving and optimization techniques inspired by principles of evolution and genetics. As any other scientific field, its success relies on the continuity provided by new researchers joining the field to help it progress. One of the most important sources for new researchers is the next generation of PhD students that are actively studying a topic relevant to this field. It is from this main observation the idea arose of providing a platform exclusively for PhD students. ER - TY - Generic T1 - Evolutionary Computation in Combinatorial Optimization, 8th European Conference T2 - Lecture Notes in Computer Science Y1 - 2008 A1 - van Hemert, Jano A1 - Cotta, Carlos ED - van Hemert, Jano ED - Cotta, Carlos KW - evolutionary computation AB - Metaheuristics have shown to be effective for difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, tabu search, simulated annealing, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, ant colony optimization and estimation of distribution algorithms. Problems solved successfully include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the travelling salesman problem, packing and cutting, satisfiability and general mixed integer programming. EvoCOP began in 2001 and has been held annually since then. It is the first event specifically dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems. Originally held as a workshop, EvoCOP became a conference in 2004. The events gave researchers an excellent opportunity to present their latest research and to discuss current developments and applications. Following the general trend of hybrid metaheuristics and diminishing boundaries between the different classes of metaheuristics, EvoCOP has broadened its scope over the last years and invited submissions on any kind of metaheuristic for combinatorial optimization. JF - Lecture Notes in Computer Science PB - Springer VL - LNCS 4972 ER - TY - CONF T1 - Exploiting data compression in collective I/O techniques. T2 - Cluster Computing 2008. Y1 - 2008 A1 - Rosa Filgueira A1 - David E. Singh A1 - Juan Carlos Pichel A1 - Jesús Carretero JF - Cluster Computing 2008. CY - Tsukuba, Japand. SN - 978-1-4244-2639-3 ER - TY - CONF T1 - e-Research Infrastructure Development and Community Engagement T2 - All Hands Meeting 2007 Y1 - 2007 A1 - Voss, A. A1 - Mascord, M. A1 - Fraser, M. A1 - Jirotka, M. A1 - Procter, R. A1 - Halfpenny, P. A1 - Fergusson, D. A1 - Atkinson, M. A1 - Dunn, S. A1 - Blanke, T. A1 - Hughes, L. A1 - Anderson, S. AB - The UK and wider international e-Research initiatives are entering a critical phase in which they need to move from the development of the basic underlying technology, demonstrators, prototypes and early applications to wider adoption and the development of stable infrastructures. In this paper we will review existing work on studies of infrastructure and community development, requirements elicitation for existing services as well as work within the arts and humanities and the social sciences to establish e-Research in these communities. We then describe two projects recently funded by JISC to study barriers to adoption and responses to them as well as use cases and service usage models. JF - All Hands Meeting 2007 CY - Nottingham, UK ER - TY - Generic T1 - European Graduate Student Workshop on Evolutionary Computation Y1 - 2007 A1 - Giacobini, Mario A1 - van Hemert, Jano ED - Mario Giacobini ED - van Hemert, Jano KW - evolutionary computation AB - Evolutionary computation involves the study of problem-solving and optimization techniques inspired by principles of evolution and genetics. As any other scientific field, its success relies on the continuity provided by new researchers joining the field to help it progress. One of the most important sources for new researchers is the next generation of PhD students that are actively studying a topic relevant to this field. It is from this main observation the idea arose of providing a platform exclusively for PhD students. CY - Valencia, Spain ER - TY - Generic T1 - Evolutionary Computation in Combinatorial Optimization, 7th European Conference T2 - Lecture Notes in Computer Science Y1 - 2007 A1 - Cotta, Carlos A1 - van Hemert, Jano ED - Carlos Cotta ED - van Hemert, Jano KW - evolutionary computation AB - Metaheuristics have often been shown to be effective for difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms, and ant colony optimization. Successfully solved problems include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the traveling salesman problem, satisfiability, packing and cutting, and general mixed integer programming. EvoCOP began in 2001 and has been held annually since then. It was the first event specifically dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems. Originally held as a workshop, EvoCOP became a conference in 2004. The events gave researchers an excellent opportunity to present their latest research and to discuss current developments and applications as well as providing for improved interaction between members of this scientific community. Following the general trend of hybrid metaheuristics and diminishing boundaries between the different classes of metaheuristics, EvoCOP has broadened its scope over the last years and invited submissions on any kind of metaheuristic for combinatorial optimization. JF - Lecture Notes in Computer Science PB - Springer VL - LNCS 4446 UR - http://springerlink.metapress.com/content/105633/ ER - TY - CONF T1 - EGEE: building a pan-European grid training organisation T2 - ACSW Frontiers Y1 - 2006 A1 - Berlich, R{\"u}diger A1 - Hardt, Marcus A1 - Kunze, Marcel A1 - Atkinson, Malcolm P. A1 - Fergusson, David JF - ACSW Frontiers ER - TY - Generic T1 - European Graduate Student Workshop on Evolutionary Computation Y1 - 2006 A1 - Giacobini, Mario A1 - van Hemert, Jano ED - Giacobini, Mario ED - van Hemert, Jano KW - evolutionary computation AB - Evolutionary computation involves the study of problem-solving and optimization techniques inspired by principles of evolution and genetics. As any other scientific field, its success relies on the continuity provided by new researchers joining the field to help it progress. One of the most important sources for new researchers is the next generation of PhD students that are actively studying a topic relevant to this field. It is from this main observation the idea arose of providing a platform exclusively for PhD students. CY - Budapest, Hungary 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 - 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 - Generic T1 - Experience with the international testbed in the crossgrid project T2 - Advances in Grid Computing-EGC 2005 Y1 - 2005 A1 - Gomes, J. A1 - David, M. A1 - Martins, J. A1 - Bernardo, L. A1 - A García A1 - Hardt, M. A1 - Kornmayer, H. A1 - Marco, Jesus A1 - Marco, Rafael A1 - Rodríguez, David A1 - Diaz, Irma A1 - Cano, Daniel A1 - Salt, J. A1 - Gonzalez, S. A1 - J Sánchez A1 - Fassi, F. A1 - Lara, V. A1 - Nyczyk, P. A1 - Lason, P. A1 - Ozieblo, A. A1 - Wolniewicz, P. A1 - Bluj, M. A1 - K Nawrocki A1 - A Padee A1 - W Wislicki ED - Peter M. A. Sloot, Alfons G. Hoekstra, Thierry Priol, Alexander Reinefeld ED - Marian Bubak JF - Advances in Grid Computing-EGC 2005 T3 - LNCS PB - Springer Berlin/Heidelberg CY - Amsterdam VL - 3470 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 - Experiences of Designing and Implementing Grid Database Services in the OGSA-DAI project T2 - Global Grid Forum Workshop on Designing and Building Grid Services/GGF9 Y1 - 2003 A1 - Antonioletti, Mario A1 - Neil Chue Hong A1 - Ally Hume A1 - Mike Jackson A1 - Krause, Amy A1 - Jeremy Nowell A1 - Charaka Palansuriya A1 - Tom Sugden A1 - Martin Westhead AB - This paper describes the experiences of the OGSA-DAI team in designing and building a database access layer using the OGSI and the emerging DAIS GGF recommendations. This middleware is designed for enabling other UK e-Science projects that require database access and providing the basic primitives for higher-level services such as Distributed Query Processing. OGSA-DAI also intends to produce one of the required reference implementations of the DAIS specification once this becomes a proposed recommendation and, until then, scope out their ideas, provide feedback as well as directly contributing to the GGF working group. This paper enumerates the issues that have arisen in tracking the DAIS and OGSI specifications whilst developing a software distribution using the Grid services model; trying to serve the needs of the various target communities; and using the Globus Toolkit OGSI core distribution. The OGSA-DAI software distribution and more details are available from the project web site at http://www.ogsadai.org.uk/. JF - Global Grid Forum Workshop on Designing and Building Grid Services/GGF9 CY - Chicago, USA ER - TY - JOUR T1 - An efficient object promotion algorithm for persistent object systems JF - Softw., Pract. Exper. Y1 - 2001 A1 - Printezis, Tony A1 - Atkinson, Malcolm P. VL - 31 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 - Evolutionary Data Conversion in the PJama Persistent Language T2 - ECOOP Workshops Y1 - 1999 A1 - Dmitriev, Misha A1 - Atkinson, Malcolm P. JF - ECOOP Workshops ER - TY - CONF T1 - Evolutionary Data Conversion in the PJama Persistent Language T2 - ECOOP Workshop on Object-Oriented Databases Y1 - 1999 A1 - Dmitriev, Misha A1 - Atkinson, Malcolm P. JF - ECOOP Workshop on Object-Oriented Databases 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 -