Autometic Generation of Dispatching Rule for Hybrid Flow Shop Scheduling based on Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Wang:2019:SMILE,

• author = "Bailin Wang and Yuzhuo Liu and Liying Hao",
• title = "Autometic Generation of Dispatching Rule for Hybrid Flow Shop Scheduling based on Genetic Programming",
• booktitle = "2019 IEEE International Conference on Smart Manufacturing, Industrial Logistics Engineering (SMILE)",
• year = "2019",
• pages = "169--173",
• month = apr,
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/SMILE45626.2019.8965274",
• abstract = "Genetic programming-based automatic heuristic generation is a hyper heuristic that can produce the key functions in a meta-heuristic for a problem. This paper studies the automatic heuristic generation method to automated generate dispatching rules for the hybrid flow shop scheduling problem, a classic scheduling problem with strong industrial background. First, a meta-heuristic based on list scheduling is given. Then a genetic programming is proposed to generate a dispatching rule which is to produce a job list in the metaheuristic. Experimental results indicate that the generated dispatching rules are superior to the classic rules.",
• notes = "Also known as \cite{8965274}",

}

Genetic Programming entries for Bailin Wang Yuzhuo Liu Liying Hao

Citations