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    ATMOS
    2009
    103views Optimization» more  ATMOS 2009»
    Efficient Route Planning in Flight Networks
    13 years 9 months ago
    Efficient Route Planning in Flight Networks
    Download  drops.dagstuhl.de
    We present a set of three new time-dependent models with increasing flexibility for realistic route planning in flight networks. By these means, we obtain small graph sizes while m...
    Daniel Delling, Thomas Pajor, Dorothea Wagner, Chr...
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    ATMOS
    2009
    105views Optimization» more  ATMOS 2009»
    Scheduling Aircraft to Reduce Controller Workload
    13 years 9 months ago
    Scheduling Aircraft to Reduce Controller Workload
    Download  www.cs.rpi.edu
    We address a problem in air traffic management: scheduling flights in order to minimize the maximum number of aircraft that simultaneously lie within a single air traffic control ...
    Joondong Kim, Alexander Kroeller, Joseph S. B. Mit...
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    ATMOS
    2009
    99views Optimization» more  ATMOS 2009»
    Edges as Nodes - a New Approach to Timetable Information
    13 years 9 months ago
    Edges as Nodes - a New Approach to Timetable Information
    Download  www.thi.uni-hannover.de
    Olaf Beyersdorff, Yevgen Nebesov
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    ATMOS
    2009
    105views Optimization» more  ATMOS 2009»
    On Assessing Robustness in Transportation Planning
    13 years 9 months ago
    On Assessing Robustness in Transportation Planning
    Download  drops.dagstuhl.de
    Abstract. We consider a fundamental problem, called QoS-aware Multicommodity Flow, for assessing robustness in transportation planning. It constitutes a natural generalization of t...
    Apostolos Bessas, Christos D. Zaroliagis
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    ICGA
    1997
    133views Optimization» more  ICGA 1997»
    Messy Genetic Algorithms for Subset Feature Selection
    13 years 10 months ago
    Messy Genetic Algorithms for Subset Feature Selection
    Download  www.cs.colostate.edu
    Subset Feature Selection problems can have severalattributes which may make Messy Genetic Algorithms an appropriateoptimization method. First, competitive solutions may often use ...
    L. Darrell Whitley, J. Ross Beveridge, Cesar Guerr...
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    ICGA
    1997
    102views Optimization» more  ICGA 1997»
    A Condition for the Genotype-Phenotype Mapping: Causality
    13 years 10 months ago
    A Condition for the Genotype-Phenotype Mapping: Causality
    Download  www.neuroinformatik.ruhr-uni-bochum.de
    Bernhard Sendhoff, Martin Kreutz, Werner von Seele...
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    ICGA
    1997
    122views Optimization» more  ICGA 1997»
    A Comparison of Global and Local Search Methods in Drug Docking
    13 years 10 months ago
    A Comparison of Global and Local Search Methods in Drug Docking
    Download  array.bioengr.uic.edu
    Molecular docking software makes computational predictions of the interaction of molecules. This can be useful, for example, in evaluating the binding of candidate drug molecules ...
    Christopher D. Rosin, R. Scott Halliday, William E...
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    ICGA
    1997
    85views Optimization» more  ICGA 1997»
    Evolving Neural Networks to Play Go
    13 years 10 months ago
    Evolving Neural Networks to Play Go
    Download  www.cse.msu.edu
    Norman Richards, David E. Moriarty, Paul McQuesten...
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    ICGA
    1997
    102views Optimization» more  ICGA 1997»
    An Experimental Analysis of Schema Creation, Propagation and Disruption in Genetic Programming
    13 years 10 months ago
    An Experimental Analysis of Schema Creation, Propagation and Disruption in Genetic Programming
    Download  cswww.essex.ac.uk
    In this paper we first review the main results in the theory of schemata in Genetic Programming (GP) and summarise a new GP schema theory which is based on a new definition of s...
    Riccardo Poli, William B. Langdon
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    ICGA
    1997
    126views Optimization» more  ICGA 1997»
    Evolution of Graph-Like Programs with Parallel Distributed Genetic Programming
    13 years 10 months ago
    Evolution of Graph-Like Programs with Parallel Distributed Genetic Programming
    Download  cswww.essex.ac.uk
    Parallel Distributed Genetic Programming (PDGP) is a new form of Genetic Programming (GP) suitable for the development of programs with a high degree of parallelism. Programs are ...
    Riccardo Poli
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