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» A framework for the description of evolutionary algorithms
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PPSN
2004
Springer
14 years 2 months ago
Dominance Based Crossover Operator for Evolutionary Multi-objective Algorithms
In spite of the recent quick growth of the Evolutionary Multi-objective Optimization (EMO) research field, there has been few trials to adapt the general variation operators to t...
Olga Rudenko, Marc Schoenauer
GECCO
2007
Springer
119views Optimization» more  GECCO 2007»
14 years 2 months ago
Optimising the flow of experiments to a robot scientist with multi-objective evolutionary algorithms
A Robot Scientist is a physically implemented system that applies artificial intelligence to autonomously discover new knowledge through cycles of scientific experimentation. Ad...
Emma Byrne
CORR
2004
Springer
153views Education» more  CORR 2004»
13 years 8 months ago
Cauchy Annealing Schedule: An Annealing Schedule for Boltzmann Selection Scheme in Evolutionary Algorithms
Abstract-Boltzmann selectionis an important selection mechanism in evolutionary algorithms as it has theoretical properties which help in theoretical analysis. However, Boltzmann s...
Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bh...
GECCO
2004
Springer
14 years 2 months ago
Systematic Integration of Parameterized Local Search Techniques in Evolutionary Algorithms
Application-specific, parameterized local search algorithms (PLSAs), in which optimization accuracy can be traded off with runtime, arise naturally in many optimization contexts....
Neal K. Bambha, Shuvra S. Bhattacharyya, Jürg...
TSMC
2010
13 years 3 months ago
Multiobjective Optimization of Temporal Processes
Abstract--This paper presents a dynamic predictiveoptimization framework of a nonlinear temporal process. Datamining (DM) and evolutionary strategy algorithms are integrated in the...
Zhe Song, Andrew Kusiak