An improved adaptive genetic algorithm based on hormone modulation mechanism for job-shop scheduling problem

@article{Wang2011AnIA,
  title={An improved adaptive genetic algorithm based on hormone modulation mechanism for job-shop scheduling problem},
  author={Lei Wang and Dunbing Tang},
  journal={Expert Syst. Appl.},
  year={2011},
  volume={38},
  pages={7243-7250}
}
An improved adaptive genetic algorithm (IAGA) for solving the minimum makespan problem of job-shop scheduling problem (JSP) is presented. Though the traditional genetic algorithm (GA) exhibits implicit parallelism and can retain useful redundant information about what is learned from previous searches by its representation in individuals in the population, yet GA may lose solutions and substructures due to the disruptive effects of genetic operators and is not easy to regulate GA’s convergence… CONTINUE READING
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Modified adaptive genetic algorithms for solving job-shop scheduling problems

  • W. L. Wang, Q. D. Wu, Y. Song
  • Systems Engineering-Theory and Practice,
  • 2004
Highly Influential
6 Excerpts

An intelligent controller based on ultra-short feedback of neuro-endocrine system

  • B. Liu, Y. S. Ding, J. H. Wang
  • Computer Simulation,
  • 2008
Highly Influential
7 Excerpts

Improved genetic algorithm for job-shop scheduling problem

  • T. K. Liu, J. T. Tsai, J. H. Chou
  • International Journal of Advanced Manufacturing…
  • 2006
Highly Influential
5 Excerpts

A genetic algorithm with modified crossover operator and search area adaptation for the job-shop scheduling problem

  • W. Masato, I. Kenichi, G. Mitsuo
  • Computers and Industrial Engineering,
  • 2005
2 Excerpts

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