Research of Assembly Job Shop Scheduling Problem Based on Modified Genetic Programming

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

@InProceedings{Lv:2017:ISCID,

• author = "Haili Lv and Guozhen Han",
• booktitle = "2017 10th International Symposium on Computational Intelligence and Design (ISCID)",
• title = "Research of Assembly Job Shop Scheduling Problem Based on Modified Genetic Programming",
• year = "2017",
• volume = "2",
• pages = "147--151",
• abstract = "The study of Job Shop Scheduling Problem (JSP) enables effective control of the production process and improves corporate economic profitability. This research extends traditional JSP to include assembly operations, which is called assembly job shop scheduling (AJSSP). AJSSP is often considered multi-objective decision problems just like JSP. This research adopts the commonly used mean total lateness as the objective for optimisation. GP (Genetic Programming) is proposed as the solution approach for AJSSP to obtain composite dispatching rules (CDR). Through experimental computation, the optimised CDR is shown to perform better than traditional simple rules including SPT, JDD and FIFO. Besides, as searching of the optimised rule is based on 85percent machine use, the performance is further tested under 80percent and 90percent load. Results confirm that the combined rule shows perfect robustness.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ISCID.2017.120",
• month = dec,
• notes = "Also known as \cite{8283244}",

}

Genetic Programming entries for Haili Lv Guozhen Han

Citations