Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2016, , 101 - 104, 26.12.2016
https://doi.org/10.18201/ijisae.267358

Öz

Kaynakça

  • A. R. Botsalı And A. Şeker, “A Scheduling and Rescheduling Algorithm for Integrated Process Planning and Scheduling Problem”, Necmettin Erbakan University, Konya, Turkey, Working paper, 2016.
  • Y. K. Kim, K. Park, and J. Ko, “A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling”, Computers & Operations Research, vol. 30, pp 1151–1171, 2003.
  • H. Lee and S. Kim, “Integration of process planning and scheduling using simulation based genetic algorithms”, International Journal of Advanced Manufacturing Technology, vol. 18, pp 586–590, 2001.
  • C. W. Leung, T. N. Wong, K. L. Mak, and R. Y. K. Fung, “Integrated process planning and scheduling by an agent-based ant colony optimization”, Computers & Industrial Engineering, vol. 59, pp 166–180, 2010.
  • S. Lv and Q. Lihong “Process planning and scheduling integration with optimal rescheduling strategies”, International Journal of Computer Integrated Manufacturing, vol. 27, pp 638–655, 2014.
  • P. Mohapatra, L. Benyoucef, and M. K. Tiwari, “Integration of process planning and scheduling through adaptive setup planning: A multi-objective approach.” International Journal of Production Research, vol. 51, pp 7190–7208, 2013.
  • C. Moon, J. Kim, and S. Hur, “Integrated process planning and scheduling with minimizing total tardiness in multi-plants supply chain”, Computers and Industrial Engineering, vol. 43, pp 331–349, 2002.
  • A. Seker, S. Erol, and R. Botsali, “A neuro-fuzzy model for a new hybrid integrated Process Planning and Scheduling system”, Expert Systems with Applications, vol. 40. pp 5341-5351, 2013.

COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM

Yıl 2016, , 101 - 104, 26.12.2016
https://doi.org/10.18201/ijisae.267358

Öz

Today flexible
manufacturing systems are highly popular due to their capability of quick
response to customer needs. Although the advantages of flexible manufacturing
systems cannot be denied, these systems also bring new issues on production
planning side. Especially assigning machines to production operations and scheduling
these operations with respect to machine constraints turn out to be an NP-Hard
problem. In this study, the integrated process routing and scheduling problem
is explained, and the performance of two different meta-heuristic techniques,
which are genetic algorithms and simulated annealing, are compared in terms of
solution time and quality.

Kaynakça

  • A. R. Botsalı And A. Şeker, “A Scheduling and Rescheduling Algorithm for Integrated Process Planning and Scheduling Problem”, Necmettin Erbakan University, Konya, Turkey, Working paper, 2016.
  • Y. K. Kim, K. Park, and J. Ko, “A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling”, Computers & Operations Research, vol. 30, pp 1151–1171, 2003.
  • H. Lee and S. Kim, “Integration of process planning and scheduling using simulation based genetic algorithms”, International Journal of Advanced Manufacturing Technology, vol. 18, pp 586–590, 2001.
  • C. W. Leung, T. N. Wong, K. L. Mak, and R. Y. K. Fung, “Integrated process planning and scheduling by an agent-based ant colony optimization”, Computers & Industrial Engineering, vol. 59, pp 166–180, 2010.
  • S. Lv and Q. Lihong “Process planning and scheduling integration with optimal rescheduling strategies”, International Journal of Computer Integrated Manufacturing, vol. 27, pp 638–655, 2014.
  • P. Mohapatra, L. Benyoucef, and M. K. Tiwari, “Integration of process planning and scheduling through adaptive setup planning: A multi-objective approach.” International Journal of Production Research, vol. 51, pp 7190–7208, 2013.
  • C. Moon, J. Kim, and S. Hur, “Integrated process planning and scheduling with minimizing total tardiness in multi-plants supply chain”, Computers and Industrial Engineering, vol. 43, pp 331–349, 2002.
  • A. Seker, S. Erol, and R. Botsali, “A neuro-fuzzy model for a new hybrid integrated Process Planning and Scheduling system”, Expert Systems with Applications, vol. 40. pp 5341-5351, 2013.
Toplam 8 adet kaynakça vardır.

Ayrıntılar

Konular Mühendislik
Bölüm Research Article
Yazarlar

Ahmet Reha Botsalı 0000-0002-8809-9353

Yayımlanma Tarihi 26 Aralık 2016
Yayımlandığı Sayı Yıl 2016

Kaynak Göster

APA Botsalı, A. R. (2016). COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM. International Journal of Intelligent Systems and Applications in Engineering, 4(Special Issue-1), 101-104. https://doi.org/10.18201/ijisae.267358
AMA Botsalı AR. COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM. International Journal of Intelligent Systems and Applications in Engineering. Aralık 2016;4(Special Issue-1):101-104. doi:10.18201/ijisae.267358
Chicago Botsalı, Ahmet Reha. “COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM”. International Journal of Intelligent Systems and Applications in Engineering 4, sy. Special Issue-1 (Aralık 2016): 101-4. https://doi.org/10.18201/ijisae.267358.
EndNote Botsalı AR (01 Aralık 2016) COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM. International Journal of Intelligent Systems and Applications in Engineering 4 Special Issue-1 101–104.
IEEE A. R. Botsalı, “COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM”, International Journal of Intelligent Systems and Applications in Engineering, c. 4, sy. Special Issue-1, ss. 101–104, 2016, doi: 10.18201/ijisae.267358.
ISNAD Botsalı, Ahmet Reha. “COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM”. International Journal of Intelligent Systems and Applications in Engineering 4/Special Issue-1 (Aralık 2016), 101-104. https://doi.org/10.18201/ijisae.267358.
JAMA Botsalı AR. COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM. International Journal of Intelligent Systems and Applications in Engineering. 2016;4:101–104.
MLA Botsalı, Ahmet Reha. “COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM”. International Journal of Intelligent Systems and Applications in Engineering, c. 4, sy. Special Issue-1, 2016, ss. 101-4, doi:10.18201/ijisae.267358.
Vancouver Botsalı AR. COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM. International Journal of Intelligent Systems and Applications in Engineering. 2016;4(Special Issue-1):101-4.

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