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» Using Genetic Algorithms for Solving Hard Problems in GIS
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EMO
2003
Springer
81views Optimization» more  EMO 2003»
14 years 1 months ago
Solving Hierarchical Optimization Problems Using MOEAs
Abstract. In this paper, we propose an approach for solving hierarchical multi-objective optimization problems (MOPs). In realistic MOPs, two main challenges have to be considered:...
Christian Haubelt, Sanaz Mostaghim, Jürgen Te...
SODA
2010
ACM
214views Algorithms» more  SODA 2010»
14 years 5 months ago
A Fourier space algorithm for solving quadratic assignment problems
The quadratic assignment problem (QAP) is a central problem in combinatorial optimization. Several famous computationally hard tasks, such as graph matching, partitioning, and the...
Risi Kondor
KBS
2006
87views more  KBS 2006»
13 years 8 months ago
Predictive and comprehensible rule discovery using a multi-objective genetic algorithm
We present a multi-objective genetic algorithm for mining highly predictive and comprehensible classification rules from large databases. We emphasize predictive accuracy and comp...
Satchidananda Dehuri, Rajib Mall
GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
14 years 1 months ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
14 years 3 days ago
A combinatorial genetic algorithm for the configuration of the 2dF/AAOmega spectrograph at the anglo-Australian observatory
To help unravel the structure of the universe, astronomers have developed systems which observe large clusters of objects at the same time. One such system is the 2-degree field s...
Steven Manos, Geraint Lewis