Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2020, , 105 - 111, 30.06.2020
https://doi.org/10.22531/muglajsci.691517

Öz

Kaynakça

  • Reference1: Alabas-Uslu, C., “A self-tuning heuristic for a multi-objective vehicle routing problem”, J Oper Res Soc, pp. pp. 988-996, 2008.
  • Reference2: Dantzig G., Fulkerson R. and Johnson S., “Solution of a large-scale travelling salesman problem”, Operations Research, 2, pp. 393-410, 1954.
  • Reference3: Ellegood, W. A., Solomon S., North J. and Campbell J. C., "School bus routing problem: Contemporary trends and research directions", Omega, in Press, 2019.
  • Reference4:Galdi, M. and Thebpanya, P.,” Optimizing school bus stop placement in Howard county, Maryland: a GIS-based heuristic approach”, Int J Appl Geospat Res, 7 (1), pp. 30-44, 2016.
  • Reference5: Kamali, B. and Mason, S.J., Pohl E.A.,”An analysis of special needs student busing”, J Public Transp, 16 (1), 2013.
  • Reference6: Kotoula, K.M. Morfoulaki, M., Aifadopoulou, G., and TzenosCalculating P.,” The optimal school bus routing and its impact on safety and environment prtection”, Transp Res Board,2647 (1), pp 142-150, 2017.
  • Reference7: Park, J. and Kim, B., “The school bus routing problem: a review”, Eur J Operat Res, 202 (2), pp. 311-319, 2010.
  • Reference8: Sarubbi, J.F. , Mesquita, C.M. , Wanner, E.F., Santos, V.F., Silva, C.M., “A strategy for clustering students minimizing the number of bus stops for solving the school bus routing problem”, Network Operations and Management Symposium (NOMS), pp. 1175-1180, 2016.
  • Reference9: Song, S.M. and Kim T. “Customer-oriented school bus operations for childcare centers in Korea”, Comp Indust Eng, 66 (1), pp. 116-124, 2013.
  • Reference10: Oluwadare, S.A., Oguntuyi, I.P. and Nwaiwu J.C., “Solving school bus routing problem using genetic algorithm-based model” Int J Intell Syst Appl, 10 (3), pp. 50-58, 2018.
  • Reference11: Toth P. and Vigo D., The vehicle routing problem, SIAM Monographs on Discrete Mathematics and Applications, Philadelphia, 2002.
  • Reference12: Unsal, O. and Yigit, T., “Using the genetic algorithm for the optimization of dynamic school bus routing problem”, Broad Res Artif Intell Neurosci, 9 (2), pp. 6-21, 2018.
  • Reference13: Uzumer, E. and Eren, T., “Okul Servisi Rotalama Problemi: Bir Uygulama”, International Journal of Engineering Research and Development, 4 (2), 2012.
  • Reference14: Yigit, T. and Unsal, O., “Using the ant colony algorithm for real-time automatic route of school buses”, Int Arab J Inform Technol, 13 (5), pp. 559-565, 2016.

EMPLOYEE SHUTTLE BUS ROUTING PROBLEM

Yıl 2020, , 105 - 111, 30.06.2020
https://doi.org/10.22531/muglajsci.691517

Öz

Recently, companies have started to use engineering techniques more than ever due to competitive market conditions, high costs, and limited budgets. To be able to reduce incurred costs and increase profitability, companies deeply analyze all the existing processes carefully. In this work, the Employee Shuttle Bus management process of an international company, which is located in Gebze, is considered, analyzed, and improved through mathematical modeling technique. Unified and Area-Based solution alternatives are developed by extending the mathematical formulation of the widely studied School Bus Routing Problem. Both proposed methods and the current situation of the company have been implemented on GAMS and solved by the CPLEX solver. It has been observed that proposed methods have provided significant cost reduction with respect to the current situation of the company. Among the newly developed methods, the Area-Based method has provided the best cost reduction amounts with less resource usage and shorter tour lengths.

Kaynakça

  • Reference1: Alabas-Uslu, C., “A self-tuning heuristic for a multi-objective vehicle routing problem”, J Oper Res Soc, pp. pp. 988-996, 2008.
  • Reference2: Dantzig G., Fulkerson R. and Johnson S., “Solution of a large-scale travelling salesman problem”, Operations Research, 2, pp. 393-410, 1954.
  • Reference3: Ellegood, W. A., Solomon S., North J. and Campbell J. C., "School bus routing problem: Contemporary trends and research directions", Omega, in Press, 2019.
  • Reference4:Galdi, M. and Thebpanya, P.,” Optimizing school bus stop placement in Howard county, Maryland: a GIS-based heuristic approach”, Int J Appl Geospat Res, 7 (1), pp. 30-44, 2016.
  • Reference5: Kamali, B. and Mason, S.J., Pohl E.A.,”An analysis of special needs student busing”, J Public Transp, 16 (1), 2013.
  • Reference6: Kotoula, K.M. Morfoulaki, M., Aifadopoulou, G., and TzenosCalculating P.,” The optimal school bus routing and its impact on safety and environment prtection”, Transp Res Board,2647 (1), pp 142-150, 2017.
  • Reference7: Park, J. and Kim, B., “The school bus routing problem: a review”, Eur J Operat Res, 202 (2), pp. 311-319, 2010.
  • Reference8: Sarubbi, J.F. , Mesquita, C.M. , Wanner, E.F., Santos, V.F., Silva, C.M., “A strategy for clustering students minimizing the number of bus stops for solving the school bus routing problem”, Network Operations and Management Symposium (NOMS), pp. 1175-1180, 2016.
  • Reference9: Song, S.M. and Kim T. “Customer-oriented school bus operations for childcare centers in Korea”, Comp Indust Eng, 66 (1), pp. 116-124, 2013.
  • Reference10: Oluwadare, S.A., Oguntuyi, I.P. and Nwaiwu J.C., “Solving school bus routing problem using genetic algorithm-based model” Int J Intell Syst Appl, 10 (3), pp. 50-58, 2018.
  • Reference11: Toth P. and Vigo D., The vehicle routing problem, SIAM Monographs on Discrete Mathematics and Applications, Philadelphia, 2002.
  • Reference12: Unsal, O. and Yigit, T., “Using the genetic algorithm for the optimization of dynamic school bus routing problem”, Broad Res Artif Intell Neurosci, 9 (2), pp. 6-21, 2018.
  • Reference13: Uzumer, E. and Eren, T., “Okul Servisi Rotalama Problemi: Bir Uygulama”, International Journal of Engineering Research and Development, 4 (2), 2012.
  • Reference14: Yigit, T. and Unsal, O., “Using the ant colony algorithm for real-time automatic route of school buses”, Int Arab J Inform Technol, 13 (5), pp. 559-565, 2016.
Toplam 14 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Semih Yalçındağ 0000-0002-6544-2657

Yayımlanma Tarihi 30 Haziran 2020
Yayımlandığı Sayı Yıl 2020

Kaynak Göster

APA Yalçındağ, S. (2020). EMPLOYEE SHUTTLE BUS ROUTING PROBLEM. Mugla Journal of Science and Technology, 6(1), 105-111. https://doi.org/10.22531/muglajsci.691517
AMA Yalçındağ S. EMPLOYEE SHUTTLE BUS ROUTING PROBLEM. Mugla Journal of Science and Technology. Haziran 2020;6(1):105-111. doi:10.22531/muglajsci.691517
Chicago Yalçındağ, Semih. “EMPLOYEE SHUTTLE BUS ROUTING PROBLEM”. Mugla Journal of Science and Technology 6, sy. 1 (Haziran 2020): 105-11. https://doi.org/10.22531/muglajsci.691517.
EndNote Yalçındağ S (01 Haziran 2020) EMPLOYEE SHUTTLE BUS ROUTING PROBLEM. Mugla Journal of Science and Technology 6 1 105–111.
IEEE S. Yalçındağ, “EMPLOYEE SHUTTLE BUS ROUTING PROBLEM”, Mugla Journal of Science and Technology, c. 6, sy. 1, ss. 105–111, 2020, doi: 10.22531/muglajsci.691517.
ISNAD Yalçındağ, Semih. “EMPLOYEE SHUTTLE BUS ROUTING PROBLEM”. Mugla Journal of Science and Technology 6/1 (Haziran 2020), 105-111. https://doi.org/10.22531/muglajsci.691517.
JAMA Yalçındağ S. EMPLOYEE SHUTTLE BUS ROUTING PROBLEM. Mugla Journal of Science and Technology. 2020;6:105–111.
MLA Yalçındağ, Semih. “EMPLOYEE SHUTTLE BUS ROUTING PROBLEM”. Mugla Journal of Science and Technology, c. 6, sy. 1, 2020, ss. 105-11, doi:10.22531/muglajsci.691517.
Vancouver Yalçındağ S. EMPLOYEE SHUTTLE BUS ROUTING PROBLEM. Mugla Journal of Science and Technology. 2020;6(1):105-11.

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