A hybrid genetic algorithm for parallel machine scheduling at semiconductor back-end production

J. Adan, A. Akcay, J. Stokkermans, R. van den Dobbelsteen

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

This paper addresses batch scheduling at a back-end semiconductor plant of Nexperia. This complex manufacturing environment is characterized by a large product and batch size variety, numerous parallel machines with large capacity differences, sequence and machine dependent setup times and machine eligibility constraints. A hybrid genetic algorithm is proposed to improve the scheduling process, the main features of which are a local search enhanced crossover mechanism, two additional fast local search procedures and a user-controlled multi-objective fitness function. Testing with real-life production data shows that this multi-objective approach can strike the desired balance between production time, setup time and tardiness, yielding high-quality practically feasible production schedules.

LanguageEnglish
Title of host publication28th International Conference on Automated Planning and Scheduling, ICAPS 2018
Pages298-302
Number of pages5
StatePublished - 1 Jan 2018
Event28th International Conference on Automated Planning and Scheduling, ICAPS 2018 - Delft, Netherlands
Duration: 24 Jun 201829 Jun 2018

Conference

Conference28th International Conference on Automated Planning and Scheduling, ICAPS 2018
CountryNetherlands
CityDelft
Period24/06/1829/06/18

Fingerprint

Genetic algorithms
Scheduling
Semiconductor materials
Testing
Hybrid genetic algorithm
Semiconductors
Parallel machine scheduling
Local search
Setup times
Fitness
Crossover
Tardiness
Parallel machines
Schedule
Batch
Manufacturing
Batch size

Cite this

Adan, J., Akcay, A., Stokkermans, J., & van den Dobbelsteen, R. (2018). A hybrid genetic algorithm for parallel machine scheduling at semiconductor back-end production. In 28th International Conference on Automated Planning and Scheduling, ICAPS 2018 (pp. 298-302)
Adan, J. ; Akcay, A. ; Stokkermans, J. ; van den Dobbelsteen, R./ A hybrid genetic algorithm for parallel machine scheduling at semiconductor back-end production. 28th International Conference on Automated Planning and Scheduling, ICAPS 2018. 2018. pp. 298-302
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Adan, J, Akcay, A, Stokkermans, J & van den Dobbelsteen, R 2018, A hybrid genetic algorithm for parallel machine scheduling at semiconductor back-end production. in 28th International Conference on Automated Planning and Scheduling, ICAPS 2018. pp. 298-302, 28th International Conference on Automated Planning and Scheduling, ICAPS 2018, Delft, Netherlands, 24/06/18.

A hybrid genetic algorithm for parallel machine scheduling at semiconductor back-end production. / Adan, J.; Akcay, A.; Stokkermans, J.; van den Dobbelsteen, R.

28th International Conference on Automated Planning and Scheduling, ICAPS 2018. 2018. p. 298-302.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Adan J, Akcay A, Stokkermans J, van den Dobbelsteen R. A hybrid genetic algorithm for parallel machine scheduling at semiconductor back-end production. In 28th International Conference on Automated Planning and Scheduling, ICAPS 2018. 2018. p. 298-302.