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» Evolving Quantum Circuits Using Genetic Algorithm
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119
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ANOR
2010
123views more  ANOR 2010»
15 years 2 months ago
Nature inspired genetic algorithms for hard packing problems
This paper presents two novel genetic algorithms (GAs) for hard industrially relevant packing problems. The design of both algorithms is inspired by aspects of molecular genetics,...
Philipp Rohlfshagen, John A. Bullinaria
97
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CEC
2005
IEEE
15 years 4 months ago
Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma
Axelrod’s original experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent P...
Timothy Gosling, Nanlin Jin, Edward P. K. Tsang
GLVLSI
2003
IEEE
134views VLSI» more  GLVLSI 2003»
15 years 7 months ago
Modeling QCA for area minimization in logic synthesis
Concerned by the wall that Moore’s Law is expected to hit in the next decade, the integrated circuit community is turning to emerging nanotechnologies for continued device impro...
Nadine Gergel, Shana Craft, John Lach
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
15 years 8 months ago
Reducing the number of transistors in digital circuits using gate-level evolutionary design
This paper shows that the evolutionary design of digital circuits which is conducted at the gate level is able to produce human-competitive circuits at the transistor level. In ad...
Zbysek Gajda, Lukás Sekanina
GECCO
2004
Springer
15 years 7 months ago
Designing Multiplicative General Parameter Filters Using Adaptive Genetic Algorithms
Multiplicative general parameter (MGP) approach to finite impulse response (FIR) filtering introduces a novel way to realize cost effective adaptive filters in compact very large s...
Jarno Martikainen, Seppo J. Ovaska