Tournament selection

As explained in Advanced Algorithms and Data Structures

Tournament selection is a genetic-algorithm technique that randomly samples individuals and selects the one with the best fitness from the sample.

How Advanced Algorithms and Data Structures covers it

How deep it goes

Defines the sampling process and gives pseudocode, but does not develop a broader parameter or complexity analysis.

Examples

Uses a 0-1 knapsack population, a tournament-selection figure, and executable-style pseudocode.

What it assumes

Assumes a population with comparable fitness values and a genetic-algorithm selection context.

What you can do after

Apply tournament selection by implementing random sampling, fitness comparison, and best-candidate retention.

How it connects

Connects selection with genetic algorithms, fitness, mating, elitism, thresholding, and roulette wheel selection.

liveBookmanning.com

Read Advanced Algorithms and Data Structures on liveBook Get the book at manning.com

Also explained in

• 

  liveBookmanning.com
  Evolutionary Deep Learning: Genetic algorithms and neural networksTournament selection is a selection method that compares randomly chosen groups of individuals and selects the highest-fitness competitor from each group.
• 

  liveBookmanning.com
  Classic Computer Science Problems in Swift: Essential techniques for practicing programmersA genetic algorithm selection technique that randomly challenges several chromosomes and selects the one with the best fitness.
• 

  liveBookmanning.com
  Optimization Algorithms: AI techniques for design, planning, and control problemsTournament selection is a survivor-selection method that randomly groups individuals and retains the best individual from each group.

Compare how 4 books explain tournament selection →

Related concepts

• selectionkind of · Selection is an evolutionary optimization operation that chooses candidate solutions for continuation or reproduction according to their fitness or quality.
• roulette-wheel selectionalternative to · Roulette-wheel selection is an evolutionary selection technique that assigns candidates probabilities proportional to their fitness, typically giving lower-fitness candidates nonzero probabilities.
• fitnessuses · Fitness is a numerical score indicating how well a candidate solution performs relative to an optimization objective.
• diversitycontrasts with · Diversity is the degree of variation among members of a set or population in relevant characteristics, perspectives, behaviors, or outcomes.
• populationuses · A population is a defined group or complete set of people, units, observations, or candidate solutions considered together in a particular context.

This explainer was generated by Manning's knowledge graph from the text of Advanced Algorithms and Data Structures. The section links point to the parts of the book it draws on.