Introduction to Evolutionary Computing

Eiben, A. E., & Smith, J. E. (2015). Introduction to Evolutionary Computing. Springer.

Type

Book

Intellectual base

Textbook

Year

2015

DOI

10.1007/978-3-662-44874-8

ISBN

9783662448731

Link

https://doi.org/10.1007/978-3-662-44874-8

Cited from

biology_ecology

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Variation Strategies
  • "Can we increase variation in low-cost domains (design, hypothesis generation) while decreasing it in high-cost domains (implementation, deployment)?"—questions Eiben and Smith (2015) treat systematically as parameter-control problems in their textbook on evolutionary computing.

    This sourceStandard textbook on evolutionary computation: treats mutation rate, selection pressure, recombination, and population size as design parameters that govern convergence and premature-convergence trade-offs.

Domain-specific

• Evolutionary Algorithm
  • … initialization, and termination as the core components of an evolutionary algorithm. Their treatment also separates major variants—genetic algorithms, evolution strategies, evolutionary programming, and genetic programming—by representation and operator choices rather than treating one subtype as the entire family.

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