Job-Shop Scheduling with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Miyashita:2000:GECCO,

• author = "Kazuo Miyashita",
• title = "Job-Shop Scheduling with Genetic Programming",
• pages = "505--512",
• year = "2000",
• publisher = "Morgan Kaufmann",
• booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000)",
• editor = "Darrell Whitley and David Goldberg and Erick Cantu-Paz and Lee Spector and Ian Parmee and Hans-Georg Beyer",
• address = "Las Vegas, Nevada, USA",
• publisher_address = "San Francisco, CA 94104, USA",
• month = "10-12 " # jul,
• keywords = "genetic algorithms, genetic programming",
• ISBN = "1-55860-708-0",
• URL = "http://gpbib.cs.ucl.ac.uk/gecco2000/GP041.pdf",
• DOI = "doi:10.5555/2933718.2933809",
• size = "8 pages",
• abstract = "In order to solve a real-time scheduling problem, a computationally intensive search-based optimization method is not practical, but the efficient dispatching rule that is well-customized for the specific problem at hand can be an effective problem solving method. A dispatching rule is scheduling heuristics that decide the sequence of operations to be executed at each resource in the scheduling problem. However, developing a customized dispatching rule for specific scheduling problems is an arduous task even for domain experts or researchers in the scheduling problem. In this research, the author views scheduling problems as multi-agent problem solving and proposes an approach for synthesizing the dispatching rule by means of Genetic Programming (GP). In the preliminary experiments, the author got the results showing that GP-based multi-agent dispatching scheduler outperformed the well-known dispatching rules.",
• notes = "A joint meeting of the ninth International Conference on Genetic Algorithms (ICGA-2000) and the fifth Annual Genetic Programming Conference (GP-2000) Part of \cite{whitley:2000:GECCO}",

}

Genetic Programming entries for Kazuo Miyashita

Citations