The Library
Evolutionary methods for the design of dispatching rules for complex and dynamic scheduling problems
Tools
Pickardt, Christoph W. (2013) Evolutionary methods for the design of dispatching rules for complex and dynamic scheduling problems. PhD thesis, University of Warwick.
|
PDF
WRAP_THESIS_Pickardt_2013.pdf - Submitted Version - Requires a PDF viewer. Download (1890Kb) | Preview |
Official URL: http://webcat.warwick.ac.uk/record=b2704739~S1
Abstract
Three methods, based on Evolutionary Algorithms (EAs), to support and automate the design
of dispatching rules for complex and dynamic scheduling problems are proposed in this thesis.
The first method employs an EA to search for problem instances on which a given dispatching
rule performs badly. These instances can then be analysed to reveal weaknesses of the
tested rule, thereby providing guidelines for the design of a better rule. The other two methods
are hyper-heuristics, which employ an EA directly to generate effective dispatching rules. In
particular, one hyper-heuristic is based on a specific type of EA, called Genetic Programming
(GP), and generates a single rule from basic job and machine attributes, while the other generates
a set of work centre-specific rules by selecting a (potentially) different rule for each
work centre from a number of existing rules. Each of the three methods is applied to some
complex and dynamic scheduling problem(s), and the resulting dispatching rules are tested
against benchmark rules from the literature. In each case, the benchmark rules are shown to be
outperformed by a rule (set) that results from the application of the respective method, which
demonstrates the effectiveness of the proposed methods.
Item Type: | Thesis (PhD) |
---|---|
Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TS Manufactures |
Library of Congress Subject Headings (LCSH): | Production scheduling -- Mathematical models, Evolutionary computation, Genetic programming (Computer science) |
Official Date: | July 2013 |
Institution: | University of Warwick |
Theses Department: | Warwick Business School |
Thesis Type: | PhD |
Publication Status: | Unpublished |
Supervisor(s)/Advisor: | Branke, Jürgen, 1969-; Chen, Bo |
Sponsors: | Deutsche Forschungsgemeinschaft (DFG) (BR 1592/7-1); Warwick Business School |
Extent: | xii, 161 leaves : charts. |
Language: | eng |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year