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» On Using Populations of Sets in Multiobjective Optimization
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CEC
2008
IEEE
15 years 6 months ago
Evolutionary Multi-objective Simulated Annealing with adaptive and competitive search direction
— In this paper, we propose a population-based implementation of simulated annealing to tackle multi-objective optimisation problems, in particular those of combinatorial nature....
Hui Li, Dario Landa Silva
ASC
2011
14 years 6 months ago
Quality of Service constrained routing optimization using Evolutionary Computation
In this work, a novel optimization framework is proposed that allows the improvement of Quality of Service levels in TCP/IP based networks, by configuring the routing weights of ...
Miguel Rocha, Pedro Sousa, Paulo Cortez, Miguel Ri...
GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
15 years 6 months ago
Crossover operators for multiobjective k-subset selection
Genetic algorithms are often applied to combinatorial optimization problems, the most popular one probably being the traveling salesperson problem. In contrast to permutations use...
Thorsten Meinl, Michael R. Berthold
EMO
2006
Springer
110views Optimization» more  EMO 2006»
15 years 3 months ago
Capabilities of EMOA to Detect and Preserve Equivalent Pareto Subsets
Recent works in evolutionary multiobjective optimization suggest to shift the focus from solely evaluating optimization success in the objective space to also taking the decision s...
Günter Rudolph, Boris Naujoks, Mike Preuss
COLT
1993
Springer
15 years 3 months ago
Learning from a Population of Hypotheses
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
Michael J. Kearns, H. Sebastian Seung