A genetic programming learning approach to generate dispatching rules for flexible shop scheduling problems

This paper deals with a Genetic Programming (GP) approach for solving flexible shop scheduling problems. The adopted approach aims to generate priority rules in the form of an expression tree for dispatching jobs. Therefore, in a list-scheduling algorithm, the available jobs can be ranked using the...

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Bibliographic Details

Published in:	International journal of production economics Vol. 243; p. 108342
Main Authors:	Braune, Roland, Benda, Frank, Doerner, Karl F., Hartl, Richard F.
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.01.2022
Subjects:	Flexible shop scheduling Genetic programming Iterative dispatching rule Machine learning Multi-tree representation Multi-tree representation Flexible shop scheduling Iterative dispatching rule Genetic programming Machine learning
ISSN:	0925-5273, 1873-7579
Online Access:	Get full text
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