A similarity measure for Straight Line Programs and its application to control diversity in Genetic Programming
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- @Article{RUEDA:2022:ESA,
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author = "R. Rueda and M. P. Cuellar and L. G. B. Ruiz and
M. C. Pegalajar",
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title = "A similarity measure for Straight Line Programs and
its application to control diversity in Genetic
Programming",
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journal = "Expert Systems with Applications",
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volume = "194",
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pages = "116415",
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year = "2022",
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ISSN = "0957-4174",
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DOI = "doi:10.1016/j.eswa.2021.116415",
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URL = "https://www.sciencedirect.com/science/article/pii/S0957417421017024",
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keywords = "genetic algorithms, genetic programming, Diversity,
Edit distance, Symbolic regression, Straight Line
Program",
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abstract = "Finding a balance between diversity and convergence
plays an important role in evolutionary algorithms to
avoid premature convergence and to perform a better
exploration of the search space. In the case of Genetic
Programming, and more specifically for symbolic
regression problems, different mechanisms have been
devised to control diversity, ranging from novel
crossover and/or mutation procedures to the design of
distance measures that help genetic operators to
increase diversity in the population. In this paper, we
start from previous works where Straight Line Programs
are used as an alternative representation to expression
trees for symbolic regression, and develop a similarity
measure based on edit distance in order to determine
how different the Straight Line Programs in the
population are. This measure is used in combination
with the CHC algorithm strategy to control diversity in
the population, and therefore to avoid local optima to
solve symbolic regression problems. The proposal is
first validated in a controlled scenario of benchmark
datasets and it is compared with previous approaches to
promote diversity in Genetic Programming. After that,
the approach is also evaluated in a real world dataset
of energy consumption data from a set of buildings of
the University of Granada",
- }
Genetic Programming entries for
Ramon Rueda Delgado
Manuel Pegalajar Cuellar
L G B Ruiz
Maria del Carmen Pegalajar Jimenez
Citations