Self-organizing neural network for adaptive operator selection in evolutionary search

Self-organizing neural network for adaptive operator selection in evolutionary search

Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other...

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Bibliographic Details
Main Authors: TENG, Teck Hou, HANDOKO, Stephanus Daniel, LAU, Hoong Chuin
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2016
Subjects:
Benchmarking
Combinatorial optimization
Evolutionary algorithms
Markov processes
Neural networks
Optimization
Artificial Intelligence and Robotics
Computer Sciences
Operations Research, Systems Engineering and Industrial Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/3404
https://ink.library.smu.edu.sg/context/sis_research/article/4405/viewcontent/SelfOrganzingNNAdaptiveOp_2016_LION.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/3404
https://ink.library.smu.edu.sg/context/sis_research/article/4405/viewcontent/SelfOrganzingNNAdaptiveOp_2016_LION.pdf

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