Optimal Recombination in Genetic Algorithms
Anton V. Eremeev, Julia V. Kovalenko
TL;DR
This paper reviews the computational complexity of the optimal recombination problem in genetic algorithms, analyzing when it can be solved efficiently or is NP-hard, based on various problem reductions and proofs.
Contribution
It provides a comprehensive survey of the complexity results for the ORP, including polynomial solvability and NP-hardness proofs, enhancing understanding of recombination operator challenges.
Findings
Identifies classes of problems with polynomial-time solutions
Establishes NP-hardness for certain recombination problems
Provides reduction techniques for analyzing ORP complexity
Abstract
This paper surveys results on complexity of the optimal recombination problem (ORP), which consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. We consider efficient reductions of the ORPs, allowing to establish polynomial solvability or NP-hardness of the ORPs, as well as direct proofs of hardness results.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMetaheuristic Optimization Algorithms Research · Evolutionary Algorithms and Applications · Scheduling and Optimization Algorithms