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A Mathematical Model and An Industrial Application for Green Vehicle Routing Problem with the Heterogeneous Fleet and Capacity Constraints

Year 2024, Volume: 27 Issue: 4, 1345 - 1352, 25.09.2024

Ali Emre Akcakoca , Emel Kızılkaya Aydogan , Yılmaz Delice , Salih Himmetoğlu

https://doi.org/10.2339/politeknik.1200084

Abstract

Today, environmental factors and sustainability concepts are taken into account along with operational criteria in Vehicle Routing Problems (VRP). The VRP that addresses environmental factors is called Green VRP (GVRP). One of the most critical factors causing global warming is carbon emissions. In GVRP, carbon emissions should be taken into account with operational costs. This study proposes a mathematical model for Green Capacity VRP (GCVRP). It is aimed to solve GCVRP by considering vehicles with different characteristics. The proposed model has been applied to determine the routes of personnel service vehicles in a furniture company. The obtained results show that the proposed mathematical model can give successful results for GCVRPs.

Keywords

GCVRP mathematical modeling sustainability green vehicle routing

References

  • [1] Dantzig G. B. and Ramser J. H., “The truck dispatching problem”, Management Science, 6(1), 80-91, (1959).
  • [2] Clarke G. and Wright, J. W. “Scheduling of vehicles from a central depot to a number of delivery points”, Operations Research, 12(4), 568-581, (1964).
  • [3] Bruglieri M., Ferone D., Festa P. and Pisacane O., “A grasp with penalty objective function for the green vehicle routing problem with private capacitated stations”, Computers and Operations Research, 143, 105770, (2022).
  • [4] Bozyer Z., Alkan A. ve Fığlalı A., “Kapasite kısıtlı araç rotalama probleminin çözümü için önce grupla sonra rotala merkezli sezgisel algoritma önerisi”, Bilişim Teknolojileri Dergisi, 7(2), 29-37, (2014).
  • [5] Kara I. and Derya T., “Polynomial size formulations for the distance and capacity constrained vehicle routing problem”, In AIP Conference Proceedings, September, American Institute of Physics, 1389(1), 1713-1718, (2011).
  • [6] Göçken T., Yaktubay M. and Kilic F., “Zaman pencereli araç rotalama problemi çözümü için çok amaçlı genetik algoritma yaklaşımı”, Gazi University Journal of Science Part C: Design and Technology, 6(4), 774-786, (2018).
  • [7] Koç Ç. and Karaoğlan İ., “Zaman bağımlı araç rotalama problemi için bir matematiksel model”, Journal of The Faculty of Engineering and Architecture of Gazi University, 29(3), (2014).
  • [8] Keskintürk T., Topuk N. ve Özyeşil O., “Araç rotalama problemleri ve çözüm yöntemleri”, İşletme Bilimi Dergisi, 3(2), 77-107, (2015).
  • [9] RamachandranPillai R. and Arock M., “Spiking neural firefly optimization scheme for the capacitated dynamic vehicle routing problem with time windows”, Neural Computing and Applications, 33(1), 409-432, (2021).
  • [10] Daneshzand F., “The vehicle-routing problem”, Logistics Operations and Management, 8, 127-153, (2011).
  • [11] Agency E. E., “Greenhouse gas emission intensity of fuels and biofuels for road transport in Europe”, European Environment Agency, 2020.
  • [12] Erdoğan S. and Miller-Hooks E., “A green vehicle routing problem”, Transportation Research Part E: Logistics and Transportation Review, 48(1), 100-114, (2012).
  • [13] Poonthalir G. and Nadarajan R., “A fuel-efficient green vehicle routing problem with varying speed constraint (F-GVRP)”, Expert Systems with Applications, 100, 131-144, (2018).
  • [14] Sawik B., Faulin J. and Pérez-Bernabeu E., “A multicriteria analysis for the green VRP: A case discussion for the distribution problem of a Spanish retailer”, Transportation Research Procedia, 22, 305-313, (2017).
  • [15] Wang L. and Lu J., “A memetic algorithm with competition for the capacitated green vehicle routing problem”, IEEE/CAA Journal of Automatica Sinica, 6(2), 516-526, (2019).
  • [16] Mehlawat M. K., Gupta P., Khaitan A. and Pedrycz W., “A hybrid intelligent approach to integrated fuzzy multiple depots capacitated green vehicle routing problem with split delivery and vehicle selection”, IEEE Transactions on Fuzzy Systems, 28(6), 1155-1166, (2019).
  • [17] Yu Y., Wang S., Wang J. and Huang, M., “A branch-and-price algorithm for the heterogeneous fleet green vehicle routing problem with time windows”, Transportation Research Part B: Methodological, 122, 511-527, (2019).
  • [18] Ren X., Huang H., Feng S. and Liang, G. “An improved variable neighborhood search for bi-objective mixed-energy fleet vehicle routing problem”, Journal of Cleaner Production, 275, 124155, (2020).
  • [19] Li Y., Soleimani H. and Zohal, M., “An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives”, Journal of Cleaner Production, 227, 1161-1172, (2019).
  • [20] Afshar-Bakeshloo M., Mehrabi A., Safari H., Maleki M. ve Jolai F., “A green vehicle routing problem with customer satisfaction criteria”, Journal of Industrial Engineering International, 12(4), 529-544, (2016).
  • [21] Abdullahi H., Reyes-Rubiano L., Ouelhadj D., Faulin J. and Juan A. A., “Modelling and multi-criteria analysis of the sustainability dimensions for the green vehicle routing problem”, European Journal of Operational Research, 292(1), 143-154, (2021).
  • [22] Nyako S. I., Tayachi D. and Tagina M., “Minimizing fuel consumption in the time-dependent VRP”, In 2022 8th IEEE International Conference on Control, Decision and Information Technologies, May, 647-652, (2022).
  • [23] Sun X., Dai X., Pan S., Bao N., Liu N. and Shi X., “A discrete teaching-learning-based optimization algorithm for the green vehicle routing problem”, 23rd IEEE Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science and Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud and Big Data Systems and Application, 1552-1557, (2021).
  • [24] Bruglieri M., Mancini S., Pezzella F. and Pisacane O., “A path-based solution approach for the green vehicle routing problem”, Computers and Operations Research, 103, 109-122, (2019).
  • [25] Matos M. R. S., Frota Y. and Ochi L. S. “Green vehicle routing and scheduling problem with split delivery”, Electronic Notes in Discrete Mathematics, 69, 13-20, (2018).
  • [26] da Costa P. R. D. O., Mauceri S., Carroll P. and Pallonetto F., “A genetic algorithm for a green vehicle routing problem”, Electronic Notes in Discrete Mathematics, 64, 65-74, (2018).
  • [27] Jabir E., Panicker V. V. and Sridharan R., “Design and development of a hybrid ant colony-variable neighborhood search algorithm for a multi- depot green vehicle routing problem”, Transportation Research Part D: Transport and Environment, 57, 422-457, (2017).
  • [28] Ferreira K. M., de Queiroz T. A. and Toledo F. M. B., “An exact approach for the green vehicle routing problem with two-dimensional loading constraints and split delivery”, Computers and Operations Research, 136, 105452, (2021).
  • [29] Asghari M. and Al-e S. M. J. M., “Green vehicle routing problem: a state-of-the-art review”, International Journal of Production Economics, 231, 107899, (2021).
  • [30] Moghdani R., Salimifard K., Demir E. and Benyettou A., “The green vehicle routing problem: a systematic literature review”, Journal of Cleaner Production, 279, 123691, (2021).
  • [31] Qi R., Li J. Q., Wang J., Jin H. and Han Y. Y., “QMOEA: A q-learning-based multi-objective evolutionary algorithm for solving time-dependent green vehicle routing problems with time windows”, Information Sciences, 608, 178-201, (2022).
  • [32] Barth M., Younglove T. and Scora, G., “Development of a heavy-duty diesel modal emissions and fuel consumption model”, US Berkley, 124, (2005).
  • [33] Bektaş T. and Laporte G., “The pollution-routing problem”, Transportation Research Part B: Methodological, 45(8), 1232-1250, (2011).
  • [34] Demir E., Bektaş T. and Laporte G., “An adaptive large neighborhood search heuristic for the pollution-routing problem”, European Journal of Operational Research, 223(2), 346-359, (2012).
  • [35] Franceschetti A., Honhon D., Van Woensel, T., Bektaş T. and Laporte G., “The time-dependent pollution-routing problem”, Transportation Research Part B: Methodological, 56, 265-293, (2013).
  • [36] Soysal M., Bloemhof-Ruwaard J. M. and Bektaş T., “The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations”, International Journal of Production Economics, 164, 366-378, (2015).
  • [37] Kısa T., Atıcı E. K. ve Ulucan A., “İki-aşamalı araç rotalama problemi: temel yaklaşımlar ve konvansiyonel araç rotalama problemi ile karşılaştırmalar”, Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 40(2), 368-403, (2021).
  • [38] Kılıç M. Y., Dönmez T. ve Adalı S., “Karayolu ulaşımında yakıt tüketimine bağlı karbon ayak izi değişimi: Çanakkale örneği”, Gümüşhane Üniversitesi Fen Bilimleri Dergisi, 11(3), 943-955, (2021).
  • [39] Kaplanseren B., Mercan B., Özdemir B., Kadıoğlu H. H. and Çağrı S. E. L., “Araç rotalamada karbon ayak izi ve endüstriyel bir uygulama”, International Journal of Engineering Research and Development, 11(1), 239-252, (2019).
  • [40] Düzakın E. ve Demircioğlu M., “Araç rotalama problemleri ve çözüm yöntemleri”, Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 13(1), (2009).

Heterojen Filolu ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model ve Endüstriyel Bir Uygulama

Year 2024, Volume: 27 Issue: 4, 1345 - 1352, 25.09.2024

Ali Emre Akcakoca , Emel Kızılkaya Aydogan , Yılmaz Delice , Salih Himmetoğlu

https://doi.org/10.2339/politeknik.1200084

Abstract

Günümüzde Araç Rotalama Problemlerinde (ARP) operasyonel kriterlerle birlikte çevresel faktörler ve sürdürülebilirlik kavramları da dikkate alınmaktadır. Çevresel faktörleri ele alarak oluşturulan ARP, Yeşil ARP (YARP) olarak adlandırılmaktadır. Küresel ısınmayı sebep olan en önemli faktörlerden biri karbon salınımıdır. YARP’de karbon salınımı operasyonel maliyetler içerisinde dikkate alınmalıdır. Bu çalışmada Yeşil Kapasiteli ARP (YKARP) için bir matematiksel model önerilmektedir. Farklı özelliklere sahip araçlar ele alınarak YKARP’nin çözülmesi amaçlanmaktadır. Önerilen model bir mobilya firmasındaki personel servis araçlarının rotalarını belirlemede uygulanmıştır. Elde edilen sonuçlar önerilen matematiksel modelin YKARP’ler için başarılı sonuçlar verebileceğini göstermektedir.

Keywords

YKARP mtematiksel modelleme sürdürülebilirlik yeşilr araç rotalama

References

  • [1] Dantzig G. B. and Ramser J. H., “The truck dispatching problem”, Management Science, 6(1), 80-91, (1959).
  • [2] Clarke G. and Wright, J. W. “Scheduling of vehicles from a central depot to a number of delivery points”, Operations Research, 12(4), 568-581, (1964).
  • [3] Bruglieri M., Ferone D., Festa P. and Pisacane O., “A grasp with penalty objective function for the green vehicle routing problem with private capacitated stations”, Computers and Operations Research, 143, 105770, (2022).
  • [4] Bozyer Z., Alkan A. ve Fığlalı A., “Kapasite kısıtlı araç rotalama probleminin çözümü için önce grupla sonra rotala merkezli sezgisel algoritma önerisi”, Bilişim Teknolojileri Dergisi, 7(2), 29-37, (2014).
  • [5] Kara I. and Derya T., “Polynomial size formulations for the distance and capacity constrained vehicle routing problem”, In AIP Conference Proceedings, September, American Institute of Physics, 1389(1), 1713-1718, (2011).
  • [6] Göçken T., Yaktubay M. and Kilic F., “Zaman pencereli araç rotalama problemi çözümü için çok amaçlı genetik algoritma yaklaşımı”, Gazi University Journal of Science Part C: Design and Technology, 6(4), 774-786, (2018).
  • [7] Koç Ç. and Karaoğlan İ., “Zaman bağımlı araç rotalama problemi için bir matematiksel model”, Journal of The Faculty of Engineering and Architecture of Gazi University, 29(3), (2014).
  • [8] Keskintürk T., Topuk N. ve Özyeşil O., “Araç rotalama problemleri ve çözüm yöntemleri”, İşletme Bilimi Dergisi, 3(2), 77-107, (2015).
  • [9] RamachandranPillai R. and Arock M., “Spiking neural firefly optimization scheme for the capacitated dynamic vehicle routing problem with time windows”, Neural Computing and Applications, 33(1), 409-432, (2021).
  • [10] Daneshzand F., “The vehicle-routing problem”, Logistics Operations and Management, 8, 127-153, (2011).
  • [11] Agency E. E., “Greenhouse gas emission intensity of fuels and biofuels for road transport in Europe”, European Environment Agency, 2020.
  • [12] Erdoğan S. and Miller-Hooks E., “A green vehicle routing problem”, Transportation Research Part E: Logistics and Transportation Review, 48(1), 100-114, (2012).
  • [13] Poonthalir G. and Nadarajan R., “A fuel-efficient green vehicle routing problem with varying speed constraint (F-GVRP)”, Expert Systems with Applications, 100, 131-144, (2018).
  • [14] Sawik B., Faulin J. and Pérez-Bernabeu E., “A multicriteria analysis for the green VRP: A case discussion for the distribution problem of a Spanish retailer”, Transportation Research Procedia, 22, 305-313, (2017).
  • [15] Wang L. and Lu J., “A memetic algorithm with competition for the capacitated green vehicle routing problem”, IEEE/CAA Journal of Automatica Sinica, 6(2), 516-526, (2019).
  • [16] Mehlawat M. K., Gupta P., Khaitan A. and Pedrycz W., “A hybrid intelligent approach to integrated fuzzy multiple depots capacitated green vehicle routing problem with split delivery and vehicle selection”, IEEE Transactions on Fuzzy Systems, 28(6), 1155-1166, (2019).
  • [17] Yu Y., Wang S., Wang J. and Huang, M., “A branch-and-price algorithm for the heterogeneous fleet green vehicle routing problem with time windows”, Transportation Research Part B: Methodological, 122, 511-527, (2019).
  • [18] Ren X., Huang H., Feng S. and Liang, G. “An improved variable neighborhood search for bi-objective mixed-energy fleet vehicle routing problem”, Journal of Cleaner Production, 275, 124155, (2020).
  • [19] Li Y., Soleimani H. and Zohal, M., “An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives”, Journal of Cleaner Production, 227, 1161-1172, (2019).
  • [20] Afshar-Bakeshloo M., Mehrabi A., Safari H., Maleki M. ve Jolai F., “A green vehicle routing problem with customer satisfaction criteria”, Journal of Industrial Engineering International, 12(4), 529-544, (2016).
  • [21] Abdullahi H., Reyes-Rubiano L., Ouelhadj D., Faulin J. and Juan A. A., “Modelling and multi-criteria analysis of the sustainability dimensions for the green vehicle routing problem”, European Journal of Operational Research, 292(1), 143-154, (2021).
  • [22] Nyako S. I., Tayachi D. and Tagina M., “Minimizing fuel consumption in the time-dependent VRP”, In 2022 8th IEEE International Conference on Control, Decision and Information Technologies, May, 647-652, (2022).
  • [23] Sun X., Dai X., Pan S., Bao N., Liu N. and Shi X., “A discrete teaching-learning-based optimization algorithm for the green vehicle routing problem”, 23rd IEEE Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science and Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud and Big Data Systems and Application, 1552-1557, (2021).
  • [24] Bruglieri M., Mancini S., Pezzella F. and Pisacane O., “A path-based solution approach for the green vehicle routing problem”, Computers and Operations Research, 103, 109-122, (2019).
  • [25] Matos M. R. S., Frota Y. and Ochi L. S. “Green vehicle routing and scheduling problem with split delivery”, Electronic Notes in Discrete Mathematics, 69, 13-20, (2018).
  • [26] da Costa P. R. D. O., Mauceri S., Carroll P. and Pallonetto F., “A genetic algorithm for a green vehicle routing problem”, Electronic Notes in Discrete Mathematics, 64, 65-74, (2018).
  • [27] Jabir E., Panicker V. V. and Sridharan R., “Design and development of a hybrid ant colony-variable neighborhood search algorithm for a multi- depot green vehicle routing problem”, Transportation Research Part D: Transport and Environment, 57, 422-457, (2017).
  • [28] Ferreira K. M., de Queiroz T. A. and Toledo F. M. B., “An exact approach for the green vehicle routing problem with two-dimensional loading constraints and split delivery”, Computers and Operations Research, 136, 105452, (2021).
  • [29] Asghari M. and Al-e S. M. J. M., “Green vehicle routing problem: a state-of-the-art review”, International Journal of Production Economics, 231, 107899, (2021).
  • [30] Moghdani R., Salimifard K., Demir E. and Benyettou A., “The green vehicle routing problem: a systematic literature review”, Journal of Cleaner Production, 279, 123691, (2021).
  • [31] Qi R., Li J. Q., Wang J., Jin H. and Han Y. Y., “QMOEA: A q-learning-based multi-objective evolutionary algorithm for solving time-dependent green vehicle routing problems with time windows”, Information Sciences, 608, 178-201, (2022).
  • [32] Barth M., Younglove T. and Scora, G., “Development of a heavy-duty diesel modal emissions and fuel consumption model”, US Berkley, 124, (2005).
  • [33] Bektaş T. and Laporte G., “The pollution-routing problem”, Transportation Research Part B: Methodological, 45(8), 1232-1250, (2011).
  • [34] Demir E., Bektaş T. and Laporte G., “An adaptive large neighborhood search heuristic for the pollution-routing problem”, European Journal of Operational Research, 223(2), 346-359, (2012).
  • [35] Franceschetti A., Honhon D., Van Woensel, T., Bektaş T. and Laporte G., “The time-dependent pollution-routing problem”, Transportation Research Part B: Methodological, 56, 265-293, (2013).
  • [36] Soysal M., Bloemhof-Ruwaard J. M. and Bektaş T., “The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations”, International Journal of Production Economics, 164, 366-378, (2015).
  • [37] Kısa T., Atıcı E. K. ve Ulucan A., “İki-aşamalı araç rotalama problemi: temel yaklaşımlar ve konvansiyonel araç rotalama problemi ile karşılaştırmalar”, Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 40(2), 368-403, (2021).
  • [38] Kılıç M. Y., Dönmez T. ve Adalı S., “Karayolu ulaşımında yakıt tüketimine bağlı karbon ayak izi değişimi: Çanakkale örneği”, Gümüşhane Üniversitesi Fen Bilimleri Dergisi, 11(3), 943-955, (2021).
  • [39] Kaplanseren B., Mercan B., Özdemir B., Kadıoğlu H. H. and Çağrı S. E. L., “Araç rotalamada karbon ayak izi ve endüstriyel bir uygulama”, International Journal of Engineering Research and Development, 11(1), 239-252, (2019).
  • [40] Düzakın E. ve Demircioğlu M., “Araç rotalama problemleri ve çözüm yöntemleri”, Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 13(1), (2009).
There are 40 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Research Article
Authors

Ali Emre Akcakoca 0000-0002-8192-4787

Emel Kızılkaya Aydogan 0000-0003-0927-6698

Yılmaz Delice 0000-0002-4654-0526

Salih Himmetoğlu 0000-0001-6081-3650

Early Pub Date July 17, 2023
Publication Date September 25, 2024
Submission Date November 6, 2022
Published in Issue Year 2024 Volume: 27 Issue: 4

Cite

APA Akcakoca, A. E., Kızılkaya Aydogan, E., Delice, Y., Himmetoğlu, S. (2024). Heterojen Filolu ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model ve Endüstriyel Bir Uygulama. Politeknik Dergisi, 27(4), 1345-1352. https://doi.org/10.2339/politeknik.1200084
AMA Akcakoca AE, Kızılkaya Aydogan E, Delice Y, Himmetoğlu S. Heterojen Filolu ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model ve Endüstriyel Bir Uygulama. Politeknik Dergisi. September 2024;27(4):1345-1352. doi:10.2339/politeknik.1200084
Chicago Akcakoca, Ali Emre, Emel Kızılkaya Aydogan, Yılmaz Delice, and Salih Himmetoğlu. “Heterojen Filolu Ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model Ve Endüstriyel Bir Uygulama”. Politeknik Dergisi 27, no. 4 (September 2024): 1345-52. https://doi.org/10.2339/politeknik.1200084.
EndNote Akcakoca AE, Kızılkaya Aydogan E, Delice Y, Himmetoğlu S (September 1, 2024) Heterojen Filolu ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model ve Endüstriyel Bir Uygulama. Politeknik Dergisi 27 4 1345–1352.
IEEE A. E. Akcakoca, E. Kızılkaya Aydogan, Y. Delice, and S. Himmetoğlu, “Heterojen Filolu ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model ve Endüstriyel Bir Uygulama”, Politeknik Dergisi, vol. 27, no. 4, pp. 1345–1352, 2024, doi: 10.2339/politeknik.1200084.
ISNAD Akcakoca, Ali Emre et al. “Heterojen Filolu Ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model Ve Endüstriyel Bir Uygulama”. Politeknik Dergisi 27/4 (September 2024), 1345-1352. https://doi.org/10.2339/politeknik.1200084.
JAMA Akcakoca AE, Kızılkaya Aydogan E, Delice Y, Himmetoğlu S. Heterojen Filolu ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model ve Endüstriyel Bir Uygulama. Politeknik Dergisi. 2024;27:1345–1352.
MLA Akcakoca, Ali Emre et al. “Heterojen Filolu Ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model Ve Endüstriyel Bir Uygulama”. Politeknik Dergisi, vol. 27, no. 4, 2024, pp. 1345-52, doi:10.2339/politeknik.1200084.
Vancouver Akcakoca AE, Kızılkaya Aydogan E, Delice Y, Himmetoğlu S. Heterojen Filolu ve Kapasite Kısıtlı Yeşil Araç Rotalama Problemi için Bir Matematiksel Model ve Endüstriyel Bir Uygulama. Politeknik Dergisi. 2024;27(4):1345-52.

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