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Tehnički vjesnik, Vol.24 No.5 Listopad 2017.

Izvorni znanstveni članak
https://doi.org/10.17559/TV-20151121212910

Integrated process planning and scheduling using genetic algorithms

Imran Ali Chaudhry   ORCID icon orcid.org/0000-0001-6726-0753 ; Department of Industrial Engineering, College of Engineering, University of Hail, Ha’il, Saudi Arabia
Muhammad Usman   ORCID icon orcid.org/0000-0003-4596-0550 ; Department of Industrial Engineering, College of Engineering, University of Hail, Ha’il, Saudi Arabia

Puni tekst: engleski, pdf (474 KB) str. 1401-1409 preuzimanja: 84* citiraj
APA 6th Edition
Chaudhry, I.A. i Usman, M. (2017). Integrated process planning and scheduling using genetic algorithms. Tehnički vjesnik, 24 (5), 1401-1409. https://doi.org/10.17559/TV-20151121212910
MLA 8th Edition
Chaudhry, Imran Ali i Muhammad Usman. "Integrated process planning and scheduling using genetic algorithms." Tehnički vjesnik, vol. 24, br. 5, 2017, str. 1401-1409. https://doi.org/10.17559/TV-20151121212910. Citirano 14.11.2018.
Chicago 17th Edition
Chaudhry, Imran Ali i Muhammad Usman. "Integrated process planning and scheduling using genetic algorithms." Tehnički vjesnik 24, br. 5 (2017): 1401-1409. https://doi.org/10.17559/TV-20151121212910
Harvard
Chaudhry, I.A., i Usman, M. (2017). 'Integrated process planning and scheduling using genetic algorithms', Tehnički vjesnik, 24(5), str. 1401-1409. doi: https://doi.org/10.17559/TV-20151121212910
Vancouver
Chaudhry IA, Usman M. Integrated process planning and scheduling using genetic algorithms. Tehnički vjesnik [Internet]. 2017 [pristupljeno 14.11.2018.];24(5):1401-1409. doi: https://doi.org/10.17559/TV-20151121212910
IEEE
I.A. Chaudhry i M. Usman, "Integrated process planning and scheduling using genetic algorithms", Tehnički vjesnik, vol.24, br. 5, str. 1401-1409, 2017. [Online]. doi: https://doi.org/10.17559/TV-20151121212910
Puni tekst: hrvatski, pdf (474 KB) str. 1401-1409 preuzimanja: 393* citiraj
APA 6th Edition
Chaudhry, I.A. i Usman, M. (2017). Integracija projektiranja tehnoloških procesa i planiranja primjenom genetičkih algoritama. Tehnički vjesnik, 24 (5), 1401-1409. https://doi.org/10.17559/TV-20151121212910
MLA 8th Edition
Chaudhry, Imran Ali i Muhammad Usman. "Integracija projektiranja tehnoloških procesa i planiranja primjenom genetičkih algoritama." Tehnički vjesnik, vol. 24, br. 5, 2017, str. 1401-1409. https://doi.org/10.17559/TV-20151121212910. Citirano 14.11.2018.
Chicago 17th Edition
Chaudhry, Imran Ali i Muhammad Usman. "Integracija projektiranja tehnoloških procesa i planiranja primjenom genetičkih algoritama." Tehnički vjesnik 24, br. 5 (2017): 1401-1409. https://doi.org/10.17559/TV-20151121212910
Harvard
Chaudhry, I.A., i Usman, M. (2017). 'Integracija projektiranja tehnoloških procesa i planiranja primjenom genetičkih algoritama', Tehnički vjesnik, 24(5), str. 1401-1409. doi: https://doi.org/10.17559/TV-20151121212910
Vancouver
Chaudhry IA, Usman M. Integracija projektiranja tehnoloških procesa i planiranja primjenom genetičkih algoritama. Tehnički vjesnik [Internet]. 2017 [pristupljeno 14.11.2018.];24(5):1401-1409. doi: https://doi.org/10.17559/TV-20151121212910
IEEE
I.A. Chaudhry i M. Usman, "Integracija projektiranja tehnoloških procesa i planiranja primjenom genetičkih algoritama", Tehnički vjesnik, vol.24, br. 5, str. 1401-1409, 2017. [Online]. doi: https://doi.org/10.17559/TV-20151121212910

Sažetak
Process planning and scheduling are two of the most important functions in any manufacturing system. Traditionally process planning and scheduling are considered as two separate functions. In this paper a Genetic Algorithm (GA) for integrated process planning and scheduling is proposed where selection of the best process plan and scheduling of jobs in a job shop environment are done simultaneously. In the proposed approach a domain independent spreadsheet based approach is presented to solve this class of problems. The precedence relations among job operations are considered in the model, based on which implicit representation of a feasible process plans for each job can be done. To verify the performance and feasibility of the presented approach, the proposed algorithm has been evaluated against a number of benchmark problems that have been adapted from the previously published literature. The experimental results show that the proposed approach can efficiently achieve optimal or near-optimal solutions for the problems adopted from literature. It is also demonstrated that the proposed algorithm is of general purpose in application and could be used for the optimisation of any objective function without changing the model or the basic GA routine.

Ključne riječi
integrated process planning and scheduling (IPPS); genetic algorithms; job shop

Hrčak ID: 188236

URI
https://hrcak.srce.hr/188236

[hrvatski]

Posjeta: 617 *