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» Solving Mastermind Using Genetic Algorithms
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CISS
2008
IEEE
14 years 3 months ago
A genetic algorithm for designing constellations with low error floors
—The error floor of bit-interleaved coded modulation with iterative decoding (BICM-ID) can be minimized for a particular constellation by maximizing the harmonic mean of the squ...
Matthew C. Valenti, Raghu Doppalapudi, Don J. Torr...
IJON
2008
177views more  IJON 2008»
13 years 8 months ago
An asynchronous recurrent linear threshold network approach to solving the traveling salesman problem
In this paper, an approach to solving the classical Traveling Salesman Problem (TSP) using a recurrent network of linear threshold (LT) neurons is proposed. It maps the classical ...
Eu Jin Teoh, Kay Chen Tan, H. J. Tang, Cheng Xiang...
JCIT
2010
172views more  JCIT 2010»
13 years 3 months ago
Conditional Sensor Deployment Using Evolutionary Algorithms
Sensor deployment is a critical issue, as it affects the cost and detection capabilities of a wireless sensor network. Although many previous efforts have addressed this issue, mo...
M. Sami Soliman, Guanzheng Tan
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
13 years 9 months ago
Dual-population genetic algorithm for nonstationary optimization
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Taejin Park, Ri Choe, Kwang Ryel Ryu
SIGADA
2004
Springer
14 years 1 months ago
Comparative analysis of genetic algorithm implementations
Genetic Algorithms provide computational procedures that are modeled on natural genetic system mechanics, whereby a coded solution is “evolved” from a set of potential solutio...
Robert Soricone, Melvin Neville