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On Natural Based Optimization

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Abstract

Nature has always been a source of great inspiration for engineers and mathematicians. Evolutionary Algorithms are the latest in a line of natural-based innovations which have had a profound effect on the application of optimization in science and engineering. Although based on nature, Evolutionary Algorithms are nonetheless distinctly different from natural evolution in several areas. This paper outlines early and recent developments of Evolutionary Algorithms while covering those areas of difference. Practical issues related to the use of Evolutionary Algorithms, key parameters that affect the quality of the search and impact of user choices in problem formulation are also covered in this paper.

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Notes

  1. A phenotype is a complete genetic package. In the biological world, phenotypes represent organism, for example humans.

  2. Non-genetic.

  3. From a finite domain \(\cal{X}\) to a finite domain \(\cal{Y}.\)

  4. The Building Block Hypothesis is classically referred to Goldberg. However, in here Holland is also referred to because in a recent paper [33], Goldberg refers to the building block hypothesis as Holland’s idea.

  5. As opposed to its ‘magnitude’ and ‘direction’.

  6. The first number is the number of parents, the second number is the number of children. The ‘+’ indicates that selection takes place between the entire population of parents and children, as opposed to ‘,’ which indicates selection among the children only.

  7. One of three, in this case.

  8. If two strings are the same, crossover simply exchanges similar information.

  9. Also referred to as elitist selection.

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    Amin Nobakhti

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Nobakhti, A. On Natural Based Optimization. Cogn Comput 2, 97–119 (2010). https://doi.org/10.1007/s12559-010-9039-2

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