Conceptual modeling of evolvable local searches in memetic algorithms using linear genetic programming: a case study on capacitated vehicle routing problem
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- @Article{journals/soco/FengOCC16,
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author = "Liang Feng and Yew-Soon Ong and Caishun Chen and
Xianshun Chen",
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title = "Conceptual modeling of evolvable local searches in
memetic algorithms using linear genetic programming: a
case study on capacitated vehicle routing problem",
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journal = "Soft Computing",
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year = "2016",
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number = "9",
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volume = "20",
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pages = "3745--3769",
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keywords = "genetic algorithms, genetic programming, Memetic
computation, Individual learning, Linear genetic
programming, Adaptive memetic algorithms, Vehicle
routing problems",
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bibdate = "2017-05-20",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/soco/soco20.html#FengOCC16",
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DOI = "doi:10.1007/s00500-015-1971-3",
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abstract = "This paper presents a study on the conceptual
modelling of memetic algorithm with evolvable local
search in the form of linear programs, self-assembled
by linear genetic programming based evolution. In
particular, the linear program structure for local
search and the associated local search self-assembling
process in the lifetime learning process of memetic
algorithm are proposed. Results showed that the memetic
algorithm with evolvable local search provides 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 meta-heuristics, on a plethora
of capacitated vehicle routing problem sets
considered.",
- }
Genetic Programming entries for
Liang Feng
Yew-Soon Ong
Caishun Chen
Xianshun Chen
Citations