Many-Objective Genetic Programming for Job-Shop Scheduling

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Masood:2022:sigevolution,

• author = "Atiya Masood",
• title = "Many-Objective Genetic Programming for Job-Shop Scheduling",
• journal = "SIGEVOlution newsletter of the ACM Special Interest Group on Genetic and Evolutionary Computation",
• year = "2022",
• volume = "15",
• number = "4",
• month = dec,
• keywords = "genetic algorithms, genetic programming, GPHH",
• ISSN = "1931-8499",
• URL = "https://evolution.sigevo.org/issues/HTML/sigevolution-15-4/index.htm#Many-Objective_Genetic_Programming_for_Job-Shop_Scheduling",
• DOI = "doi:10.1145/3584367.3584370",
• size = "4 pages",
• abstract = "Summary of PhD dissertation \cite{Masood:thesis} representing the first effort at many-objective optimization in job shop scheduling (JSS). It develops genetic programming hyperheuristic (GP-HH) approaches to evolve effective dispatching rules for many conflicting objectives in JSS problems. The aim is to develop GP-HH methods that alleviate issues related to many-objective optimisation in JSS problems and evolve new effective dispatching rules capable of enhancing job shops productivity.",
• notes = "https://evolution.sigevo.org/",

}

Genetic Programming entries for Atiya Masood

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