Elitism
Elitism is an evolutionary strategy that preserves high-performing individuals unchanged when forming the next generation.
Advanced Algorithms and Data Structures
Elitism is a genetic-algorithm strategy that copies selected high-quality individuals to the next population without alteration.
- How it is used
- Preserves high-fitness individuals across genetic-algorithm generations while the rest of the population is replaced.
- How deep it goes
- Defines the transfer rule and its effect on best fitness, but gives no dedicated elitism implementation or cost analysis.
- Examples
- Uses a 0–1 knapsack diagram and traveling-salesperson operator-rate experiments to illustrate preservation and its limits.
- What you can do after
- Operate/configure it by carrying selected top-fitness individuals forward unchanged and checking whether that choice helps the problem.
Read how Advanced Algorithms and Data Structures explains elitism →
Optimization Algorithms: AI techniques for design, planning, and control problems
Elitist selection is a survivor-selection method that retains the best individuals from the existing population and newly generated offspring.
- How it is used
- Preserves high-fitness solutions across generations during genetic-algorithm survivor selection.
- How deep it goes
- Explains selection from old and new populations, ranking, and diversity trade-offs, then works through a ticket-pricing table.
- Examples
- Uses a ticket-pricing population with binary chromosomes, objective values, crossover offspring, mutation offspring, rankings, and selected survivors.
- What you can do after
- Apply elitist selection by ranking old individuals and offspring, preserving the strongest candidates while monitoring diversity loss.
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 selectionuses · Roulette-wheel selection is an evolutionary selection technique that assigns candidates probabilities proportional to their fitness, typically giving lower-fitness candidates nonzero probabilities.
- tournament selectionuses · Tournament selection is an evolutionary technique that randomly samples groups of candidate solutions and selects the highest-fitness candidate from each group.
- rank selectionuses · Rank selection is an evolutionary selection technique that assigns selection probabilities according to individuals’ relative fitness rankings rather than raw fitness values.
- crossovercontrasts with · Crossover is an evolutionary recombination technique that combines material from parent candidate solutions to produce one or more offspring.
- diversitycontrasts with · Diversity is the degree of variation among members of a set or population in relevant characteristics, perspectives, behaviors, or outcomes.
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