Order crossover

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

A permutation crossover operator that preserves the relative order of elements from a parent while combining genetic material from two parents.

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

How deep it goes

Specifies crossover points, segment copying, wraparound scanning, duplicate exclusion, and reciprocal offspring construction.

Examples

Uses a figure showing the numbered sequence of elements added from one parent to construct an offspring.

What it assumes

Assumes chromosomes represented as permutations and two parent solutions supplied for recombination.

What you can do after

Apply OX1 by selecting segments and filling offspring in parent-preserved order without duplicate elements.

How it connects

Contrasts with partially mapped crossover, edge crossover, and cycle crossover.

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Also explained in

• 

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  Evolutionary Deep Learning: Genetic algorithms and neural networksOrdered crossover combines parent sequences while preserving the relative order of selected elements.

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Related concepts

• crossoverkind of · Crossover is an evolutionary recombination technique that combines material from parent candidate solutions to produce one or more offspring.
• edge crossoveralternative to · A permutation crossover operator that constructs offspring by preserving adjacency and connectivity information from parent permutations.
• cycle crossoveralternative to · Cycle crossover is a permutation-preserving genetic operator that partitions positional mappings between parent permutations into cycles and recombines them to produce offspring.

This explainer was generated by Manning's knowledge graph from the text of Optimization Algorithms: AI techniques for design, planning, and control problems. The section links point to the parts of the book it draws on.