A Robust Meta-Hyper-Heuristic Approach to Hybrid Flow-Shop Scheduling

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Jose Antonio {Vazquez Rodriguez} and Abdellah Salhi",
  title =        "A Robust Meta-Hyper-Heuristic Approach to Hybrid
                 Flow-Shop Scheduling",
  booktitle =    "Evolutionary Scheduling",
  publisher =    "Springer",
  year =         "2007",
  editor =       "Keshav P. Dahal and Kay Chen Tan and 
                 Peter I. Cowling",
  volume =       "49",
  series =       "Studies in Computational Intelligence",
  pages =        "125--142",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-540-48584-1",
  DOI =          "doi:10.1007/978-3-540-48584-1_5",
  abstract =     "Combining meta-heuristics and specialised methods is a
                 common strategy to generate effective heuristics. The
                 inconvenience of this practice, however, is that,
                 often, the resulting hybrids are ineffective on related
                 problems. Moreover, frequently, a high cost must be
                 paid to develop such methods. To overcome these
                 limitations, the idea of using a hyper-heuristic to
                 generate information to assist a meta-heuristic, is
                 explored. The devised approach is tested on the Hybrid
                 Flow Shop (HFS) scheduling problem in 8 different
                 forms, each with a different objective function.
                 Computational results suggest that this approach is
                 effective on all 8 problems considered. Its performance
                 is also comparable to that of specialised methods for
                 HFS with a particular objective function.",

Genetic Programming entries for Jose Antonio Vazquez Rodriguez Abdel Salhi