Dual-Sequenced Real Coded Genetic Algorithm for Picking Process Optimization

Li Yi Zheng; Shi Ping Guo; Rong Fu Zhang

doi:10.4028/www.scientific.net/AMR.1083.207

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Testing Level Measurement Devices by Imitating Sensor Signals
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IV-Characteristics Measurement Error Resulting from Long Cables for Irradiated Bipolar Junction Transistors
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Numerical Simulation of Oblique Towing Tests and Rotating Arm Tests for a Submarine Model in Same Grid Topology
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A New Test Environment Approach to SEE Detection in MOSFETs
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Dual-Sequenced Real Coded Genetic Algorithm for Picking Process Optimization
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 1083Dual-Sequenced Real Coded Genetic Algorithm for...

Dual-Sequenced Real Coded Genetic Algorithm for Picking Process Optimization

Abstract:

Automatic monoclonal colony picking machine with 96-probe picking module were employed to improve picking efficacy. The paper proposes a modified genetic algorithm based on dual-sequenced real coded andnew crossover operator to reduce the moving distance of the picking module in picking process. The algorithm makes the picking process more efficient. It also has good convergence speed and outstanding ability to overcome the premature convergence.

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Periodical:

Advanced Materials Research (Volume 1083)

Pages:

207-210

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1083.207

Citation:

Cite this paper

Online since:

January 2015

Authors:

Li Yi Zheng*, Shi Ping Guo, Rong Fu Zhang

Keywords:

Edge Information, Genetic Algorithm (GA), Optimization, Real-Valued Coding

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* - Corresponding Author

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