Genetic algorithm parenting fitness

The evolution scheme phase, in which the genetic algorithms select individuals that will form the new population, had an important impact on these algorithms.  Many approaches exist in the literature.  However, these approaches consider only the value of the fitness function to differenciate best solutions from the worst ones.  This article introduces the parenting fitness, a novel parameter, that defines the capacity of an individual to produce fittest offsprings.  Combining the standard fitness function and the parenting fitness helps the genetic algorithm to be more efficient, hence, producing best results.

 

  1. Holland J. H.  Adaptation in Natural and Artificial Systems. University of Michigan Press (1975).
  2. Vose M. D.  The Simple Genetic Algorithm: Foundations and Theory.  Complex Adaptive Systems. MIT Press (1999).
  3. Goldberg D. E.  Genetic Algorithms in Search, Optimization and Machine Learning.  Addison-Wesley Publishing Company, Inc. (1989).
  4. Kenneth E., Kinnear Jr.  Advances in Genetic Programming. MIT Press (1994).
  5. Goldberg D. E., Kalyanmoy D.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms.  Foundations of Genetic Algorithms.  1, 69–93 (1991).
  6. Moscato P.  On genetic crossover operators for relative order preservation.  C3P Report (1989).
  7. Syswerda G.  Uniform Crossover in Genetic Algorithms.  Proceedings of the 3rd International Conference on Genetic Algorithms. 2–9 (1989).
  8. Saini N.  Review of Selection Methods in Genetic Algorithms.  International Journal of Engineering and Computer Science.  6 (12), 22261–22263 (2017).
  9. Dianati M., Song I., Treiber M.  An Introduction to Genetic Algorithms and Evolution Strategies (2002).
  10. McCall J.  Genetic algorithms for modelling and optimisation.  Journal of Computational and Applied Mathematics.  184 (1), 205–222 (2005).
  11. De J K. A.  An Analysis of the Behavior of a Class of Genetic Adaptive Systems  (1975).
  12. Dantzig G. B., Ramser J. H.  The Truck Dispatching Problem.  Management Science.  6 (1), 80–91 (1959).
  13. Laporte G.  The vehicle routing problem: An overview of exact and approximate algorithms.  European Journal of Operational Research.  59 (3), 345–358 (1992).
  14. Sacramento D.  Vehicle Routing Problem with Drones Instances.  https://zenodo.org/record/1403150.
  15. Murray C. C., Chu A. G.  The Flying Sidekick Traveling Salesman Problem: Optimization of Drone-assisted Parcel Delivery.  Transportation Research Part C: Emerging Technologies.  54, 86–109 (2015).