A conceptual modeling of meme complexes in stochastic search
In science, gene provides the instruction for making proteins, while meme is the sociocultural equivalent of a gene containing instructions for carrying out behavior. Taking inspiration from nature, we model the memeplex in search as instructions that specify the coadapted meme complexes of individu...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/102283 http://hdl.handle.net/10220/16521 |
| _version_ | 1811689369768034304 |
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| author | Chen, Xianshun Ong, Yew Soon |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Chen, Xianshun Ong, Yew Soon |
| author_sort | Chen, Xianshun |
| collection | NTU |
| description | In science, gene provides the instruction for making proteins, while meme is the sociocultural equivalent of a gene containing instructions for carrying out behavior. Taking inspiration from nature, we model the memeplex in search as instructions that specify the coadapted meme complexes of individuals in their lifetime. In particular, this paper presents a study on the conceptual modeling of meme complexes or memeplexes for more effective problem solving in the context of modern stochastic optimization. The memeplex representation, credit assignment criteria for meme coadaptation, and the role of emergent memeplexes in the lifetime learning process of a memetic algorithm in search are presented. A coadapted memetic algorithm that takes the proposed conceptual modeling of memeplexes into actions to solve capacitated vehicle routing problems (CVRPs) of diverse characteristics is then designed. Results showed that adaptive memeplexes provide a means of creating highly robust, self-configuring, and scalable algorithms, thus generating improved or competitive results when benchmarking against several existing adaptive or human-designed state-of-the-art memetic algorithms and metaheuristics, on a plethora of CVRP sets considered. |
| first_indexed | 2024-10-01T05:47:01Z |
| format | Journal Article |
| id | ntu-10356/102283 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:47:01Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1022832020-05-28T07:17:24Z A conceptual modeling of meme complexes in stochastic search Chen, Xianshun Ong, Yew Soon School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity In science, gene provides the instruction for making proteins, while meme is the sociocultural equivalent of a gene containing instructions for carrying out behavior. Taking inspiration from nature, we model the memeplex in search as instructions that specify the coadapted meme complexes of individuals in their lifetime. In particular, this paper presents a study on the conceptual modeling of meme complexes or memeplexes for more effective problem solving in the context of modern stochastic optimization. The memeplex representation, credit assignment criteria for meme coadaptation, and the role of emergent memeplexes in the lifetime learning process of a memetic algorithm in search are presented. A coadapted memetic algorithm that takes the proposed conceptual modeling of memeplexes into actions to solve capacitated vehicle routing problems (CVRPs) of diverse characteristics is then designed. Results showed that adaptive memeplexes provide a means of creating highly robust, self-configuring, and scalable algorithms, thus generating improved or competitive results when benchmarking against several existing adaptive or human-designed state-of-the-art memetic algorithms and metaheuristics, on a plethora of CVRP sets considered. 2013-10-16T04:47:33Z 2019-12-06T20:52:38Z 2013-10-16T04:47:33Z 2019-12-06T20:52:38Z 2012 2012 Journal Article Chen, X. S., & Ong, Y. S. (2012). A conceptual modeling of meme complexes in stochastic search. IEEE transactions on systems, man, and cybernetics, part c (applications and reviews), 42(5), 612-625. https://hdl.handle.net/10356/102283 http://hdl.handle.net/10220/16521 10.1109/TSMCC.2012.2188832 en IEEE transactions on systems, man, and cybernetics, part c (applications and reviews) |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity Chen, Xianshun Ong, Yew Soon A conceptual modeling of meme complexes in stochastic search |
| title | A conceptual modeling of meme complexes in stochastic search |
| title_full | A conceptual modeling of meme complexes in stochastic search |
| title_fullStr | A conceptual modeling of meme complexes in stochastic search |
| title_full_unstemmed | A conceptual modeling of meme complexes in stochastic search |
| title_short | A conceptual modeling of meme complexes in stochastic search |
| title_sort | conceptual modeling of meme complexes in stochastic search |
| topic | DRNTU::Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity |
| url | https://hdl.handle.net/10356/102283 http://hdl.handle.net/10220/16521 |
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