Partially mapped crossover
Partially mapped crossover is a permutation-preserving genetic operator that exchanges parent segments and maps displaced elements to avoid duplicates and omissions.
Evolutionary Deep Learning: Genetic algorithms and neural networks
Partially matched crossover recombines indexed parent sequences while preserving matching positional relationships between exchanged segments.
- How it is used
- Uses indexed-sequence recombination when preserving positional relationships matters during genetic-algorithm evolution.
- How deep it goes
- Defines the operator, compares variants, and evaluates offspring through genealogy plots without detailing implementation code.
- Examples
- Uses indexed gene sequences, contrasting crossover operators, and genealogy plots showing offspring across generations.
- What you can do after
- Evaluate crossover choices with genealogy plots and select operators suited to indexed sequences.
Optimization Algorithms: AI techniques for design, planning, and control problems
A permutation crossover operator that combines parent segments while mapping displaced elements to preserve feasible offspring permutations.
- How it is used
- Combines permutation parents in genetic algorithms while preserving feasible offspring.
- How deep it goes
- Defines the mapping procedure, illustrates it on eight cities, and provides Python implementation guidance.
- Examples
- Uses an eight-city TSP mapping example, PMX diagrams, and a Python function that generates two offspring.
- What you can do after
- Build it from scratch by implementing segment copying, positional mapping, duplicate resolution, and offspring completion.
Related concepts
- crossoverkind of · Crossover is an evolutionary recombination technique that combines material from parent candidate solutions to produce one or more offspring.
- Traveling Salesman problemuses · The Traveling Salesman problem is a combinatorial optimization problem that seeks a minimum-cost tour visiting each specified location exactly once and returning to the starting location.
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