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Rank selection

As explained in Optimization Algorithms: AI techniques for design, planning, and control problems

A selection strategy that assigns probabilities according to individuals' relative fitness ranks rather than their absolute fitness values.

Rank selection chooses genetic-algorithm individuals by relative fitness rank rather than absolute fitness. It limits domination by a single exceptionally fit individual and helps preserve population diversity. section 7.3.3

Ticket-pricing population

Five candidate solutions are ranked by objective value: x4 is best, followed by x3, x2, x5, and x1. Rank-based selection then gives probabilities according to these positions instead of directly copying the large differences in objective values.

A practical application follows these steps:

  • Sort the population from weakest to strongest fitness and assign ranks. section 7.3.3
  • Choose linear or nonlinear ranking and set selection pressure; linear ranking uses 1.0 < SP ≤ 2.0. section 7.3.3
  • Use the resulting probabilities for parent selection, accepting lower-fitness individuals often enough to reduce bias and maintain diversity. section 7.3.3

How Optimization Algorithms: AI techniques for design, planning, and control problems covers it

How deep it goes
Explains ranking, linear and nonlinear pressure, and a worked population example, but does not provide implementation code.
Examples
Uses five ticket-pricing candidate solutions with objective values, binary encodings, ranks, and selection-probability tables.
What it assumes
Assumes genetic-algorithm populations, fitness, and selection, while illustrating the distinction between absolute and relative fitness.
What you can do after
Apply rank-based parent selection by ranking a population and tuning linear or nonlinear selection pressure.
How it connects
Connects fitness-proportional selection, selective pressure, population diversity, stochastic universal sampling, and tournament selection.
Cover of Optimization Algorithms: AI techniques for design, planning, and control problems
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