Research of Assembly Job Shop Scheduling Problem Based on Modified Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @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