TY - CHAP

T1 - Towards improved dispatching rules for complex shop floor scenarios - A genetic programming approach

AU - Hildebrandt, Torsten

AU - Heger, Jens

AU - Scholz-Reiter, Bernd

N1 - Conference code: 12

PY - 2010

Y1 - 2010

N2 - Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and objectives automatic rule search mechanism are investigated. In this paper an approach using Genetic Programming (GP) is presented. The priority rules generated by GP are evaluated on dynamic job shop scenarios from literature and compared with manually developed rules yielding very promising results also interesting for Simulation Optimization in general.

AB - Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and objectives automatic rule search mechanism are investigated. In this paper an approach using Genetic Programming (GP) is presented. The priority rules generated by GP are evaluated on dynamic job shop scenarios from literature and compared with manually developed rules yielding very promising results also interesting for Simulation Optimization in general.

KW - Dispatching rules

KW - Genetic programming

KW - Job shop scheduling

KW - Stochastic system optimization

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=77955890955&partnerID=8YFLogxK

U2 - 10.1145/1830483.1830530

DO - 10.1145/1830483.1830530

M3 - Article in conference proceedings

AN - SCOPUS:77955890955

SN - 978-1-4503-0072-8

SP - 257

EP - 264

BT - Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10

PB - Association for Computing Machinery, Inc

CY - New York

T2 - 12th Annual Genetic and Evolutionary Computation Conference - 2010

Y2 - 7 July 2010 through 11 July 2010

ER -