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

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@InCollection{Vazquez-Rodriguez:2007:EvoSchd,

• 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

Citations