Scheduling for a container supply chain to minimize costs using the meta-innovation approach
In this study, a problem of scheduling shipping lines for a container supply chain is addressed in order to minimize the costs of charging ships and the cost of maintaining the inventory of empty containers in the port by considering the time window of the port and the amount of fuel. This is a hard...
- Autores:
-
Husein, Ismail
Suhada, Arif
Chetthamrongchai, Paitoon
Peressypki, Andrej P.
Nurrohkayati, Anis Siti
Hoang Ca, Vo
Huynh Tan, Hoi
Grimaldo Guerrero, John William
M. Kavitha, M.
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/9113
- Acceso en línea:
- https://hdl.handle.net/11323/9113
https://doi.org/10.7232/iems.2021.20.4.662
https://repositorio.cuc.edu.co/
- Palabra clave:
- Transport network transport network design
Container supply chain
Line scheduling
Genetic algorithm
- Rights
- openAccess
- License
- Atribución 4.0 Internacional (CC BY 4.0)
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| dc.title.eng.fl_str_mv |
Scheduling for a container supply chain to minimize costs using the meta-innovation approach |
| title |
Scheduling for a container supply chain to minimize costs using the meta-innovation approach |
| spellingShingle |
Scheduling for a container supply chain to minimize costs using the meta-innovation approach Transport network transport network design Container supply chain Line scheduling Genetic algorithm |
| title_short |
Scheduling for a container supply chain to minimize costs using the meta-innovation approach |
| title_full |
Scheduling for a container supply chain to minimize costs using the meta-innovation approach |
| title_fullStr |
Scheduling for a container supply chain to minimize costs using the meta-innovation approach |
| title_full_unstemmed |
Scheduling for a container supply chain to minimize costs using the meta-innovation approach |
| title_sort |
Scheduling for a container supply chain to minimize costs using the meta-innovation approach |
| dc.creator.fl_str_mv |
Husein, Ismail Suhada, Arif Chetthamrongchai, Paitoon Peressypki, Andrej P. Nurrohkayati, Anis Siti Hoang Ca, Vo Huynh Tan, Hoi Grimaldo Guerrero, John William M. Kavitha, M. |
| dc.contributor.author.spa.fl_str_mv |
Husein, Ismail Suhada, Arif Chetthamrongchai, Paitoon Peressypki, Andrej P. Nurrohkayati, Anis Siti Hoang Ca, Vo Huynh Tan, Hoi Grimaldo Guerrero, John William M. Kavitha, M. |
| dc.subject.proposal.eng.fl_str_mv |
Transport network transport network design Container supply chain Line scheduling Genetic algorithm |
| topic |
Transport network transport network design Container supply chain Line scheduling Genetic algorithm |
| description |
In this study, a problem of scheduling shipping lines for a container supply chain is addressed in order to minimize the costs of charging ships and the cost of maintaining the inventory of empty containers in the port by considering the time window of the port and the amount of fuel. This is a hard-NP problem and cannot be solved on a large scale with precise methods in a logical time. Therefore, to solve and optimize the model, a meta-innovative algorithm, genetic algorithm, has been used. Also, to increase the effectiveness of the genetic algorithm, the parameters of the algorithm are adjusted using the Taguchi method. Finally, a number of problems have been solved to show the performance of this algorithm and its computational results have been compared with the results obtained from GAMS software. |
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2021 |
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2021 |
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2022-04-05T12:47:58Z |
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2022-04-05T12:47:58Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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http://purl.org/coar/resource_type/c_6501 |
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1598-7248 |
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https://hdl.handle.net/11323/9113 |
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https://doi.org/10.7232/iems.2021.20.4.662 |
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10.7232/iems.2021.20.4.662 |
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2234-6473 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
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1598-7248 10.7232/iems.2021.20.4.662 2234-6473 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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https://hdl.handle.net/11323/9113 https://doi.org/10.7232/iems.2021.20.4.662 https://repositorio.cuc.edu.co/ |
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eng |
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eng |
| dc.relation.ispartofjournal.spa.fl_str_mv |
Industrial Engineering and Management Systems |
| dc.relation.references.spa.fl_str_mv |
Alharbi, A, Wang, S., and Davy, P. (2014), Schedule design for sustainable container supply chain net works with port time windows, Advanced Engineer ing Informatics 29(3), Available from: https://doi.org/10.1016/j.aei.2014.12.001. Brour, B. D., Dirksen, J., Pisinger, D., Plum, C. E. M., and Vaaben , B. (2013), The vessel Schedule recovery problema (VSRP) – A MIP model for handling disruptions in liner shipping, European Journal of Operational Research. 224(2), 362-374 Chang, D., Jiang, Z., Yan, W., and He, J. (2010), Integrating berth allocation and quay crane assignments, Transportation Research Part E: Logistics and Transportation Review, 46(6). 975-990. Chang, D., Jiang, Z., Yan, W., and He, J. (2011), Developing a Dynamic rolling-horizon decision strategy for yard crane schededuling, Advanced Engineering Informatics, 25(3), 485-494. Du, Y., Chen Q., Quan X., Long L., and Fung, R. Y. K. (2011), Bertha allocation considering fuel consump tion and vessel emissions, Transportation Research Part E: Logistics and Transportation Review, 47(6), 1021-1037. He, J., Chang, D., Mi, W., and Yan, W. (2010), A hybrid parallel genetic algorithm for yard crane scheduling, Transportation Research Part E: Logistics and Transportation Review, 46(1), 136-155. Lei, N. (2022), Intelligent logistics scheduling model and algorithm based on internet of things technology, Alexandria Engineering Journal, 61(1), 893-903. Qi, X. and Song, D. P. (2012), Minimizing fuel emissions by optimizing vessel schedules in liner shipping with uncertain port times, Transportation Research Part E: Logistics and Transportation Review, 48(4), 863-880. Salido, M. A., Rodriguez-Molins, M., and Barber, F. (2011), Integrated intelligent techniques for remarshaling and berthing in maritime terminals, Advanced Engineering Informatics, 25(3), 435-451. Sun, Z., Lee, L. H., Chew, E. P., and Tan, K. C. (2012), MicroPort: A general simulation platform for seaport container terminals, Advanced Engineering Informatics, 26(1), 80-89. Trappey, C. V., Lin, G. Y., Trappey, A. J., Liu, C. S., and Lee, W. T. (2011), Deriving industrial logistics hub reference models for manufacturing based economies, Expert Systems with Applications, 38(2), 1223-1232. Wang, S. and Meng, Q. (2012), Liner ship route schedule design with sea contingency time and port time uncertainty, Transportation Research Part B: Methodological, 46(5), 615-633. Wang, S., Alharbi, A., and Davy, P. (2014), Liner ship route schedule design with port time windows, Transportation Research Part C: Emerging Technologies, 41, 1-17. Wang, S., Alharbi, A., and Davy, P. (2015), Ship route schedule based interactions between container shipping lines and port operators. In: C.-Y. Lee, Q. Meng (Eds.), Handbook of Ocean Container Transport Logistics: Making Global Supply Chains Effective, International Series in Operations Research & Management Science, Elsevier, Vol. 220, 279-313, Available from: http://dx.doi.org/10.1007/978-3-319 -11891-8_10. Yan, S., Chen, C.-Y., and Lin, S.-C. (2009), Ship scheduling and container shipment planning for liners in short-term operations, Journal of Marine Science and Technology, 14(4), 417-435. Yin, X. F., Khoo, L. P., and Chen, C.- H. (2011), A distributed agent system for port planning and scheduling, Advanced Engineering Informatics, 25(3), 403-412. |
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Husein, IsmailSuhada, ArifChetthamrongchai, PaitoonPeressypki, Andrej P.Nurrohkayati, Anis SitiHoang Ca, VoHuynh Tan, HoiGrimaldo Guerrero, John WilliamM. Kavitha, M.2022-04-05T12:47:58Z2022-04-05T12:47:58Z20211598-7248https://hdl.handle.net/11323/9113https://doi.org/10.7232/iems.2021.20.4.66210.7232/iems.2021.20.4.6622234-6473Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/In this study, a problem of scheduling shipping lines for a container supply chain is addressed in order to minimize the costs of charging ships and the cost of maintaining the inventory of empty containers in the port by considering the time window of the port and the amount of fuel. This is a hard-NP problem and cannot be solved on a large scale with precise methods in a logical time. Therefore, to solve and optimize the model, a meta-innovative algorithm, genetic algorithm, has been used. Also, to increase the effectiveness of the genetic algorithm, the parameters of the algorithm are adjusted using the Taguchi method. Finally, a number of problems have been solved to show the performance of this algorithm and its computational results have been compared with the results obtained from GAMS software.10 páginasapplication/pdfengAtribución 4.0 Internacional (CC BY 4.0)© 2021 KIIEhttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Scheduling for a container supply chain to minimize costs using the meta-innovation approachArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionSouth KoreaIndustrial Engineering and Management SystemsAlharbi, A, Wang, S., and Davy, P. (2014), Schedule design for sustainable container supply chain net works with port time windows, Advanced Engineer ing Informatics 29(3), Available from: https://doi.org/10.1016/j.aei.2014.12.001.Brour, B. D., Dirksen, J., Pisinger, D., Plum, C. E. M., and Vaaben , B. (2013), The vessel Schedule recovery problema (VSRP) – A MIP model for handling disruptions in liner shipping, European Journal of Operational Research. 224(2), 362-374Chang, D., Jiang, Z., Yan, W., and He, J. (2010), Integrating berth allocation and quay crane assignments, Transportation Research Part E: Logistics and Transportation Review, 46(6). 975-990.Chang, D., Jiang, Z., Yan, W., and He, J. (2011), Developing a Dynamic rolling-horizon decision strategy for yard crane schededuling, Advanced Engineering Informatics, 25(3), 485-494.Du, Y., Chen Q., Quan X., Long L., and Fung, R. Y. K. (2011), Bertha allocation considering fuel consump tion and vessel emissions, Transportation Research Part E: Logistics and Transportation Review, 47(6), 1021-1037.He, J., Chang, D., Mi, W., and Yan, W. (2010), A hybrid parallel genetic algorithm for yard crane scheduling, Transportation Research Part E: Logistics and Transportation Review, 46(1), 136-155.Lei, N. (2022), Intelligent logistics scheduling model and algorithm based on internet of things technology, Alexandria Engineering Journal, 61(1), 893-903.Qi, X. and Song, D. P. (2012), Minimizing fuel emissions by optimizing vessel schedules in liner shipping with uncertain port times, Transportation Research Part E: Logistics and Transportation Review, 48(4), 863-880.Salido, M. A., Rodriguez-Molins, M., and Barber, F. (2011), Integrated intelligent techniques for remarshaling and berthing in maritime terminals, Advanced Engineering Informatics, 25(3), 435-451.Sun, Z., Lee, L. H., Chew, E. P., and Tan, K. C. (2012), MicroPort: A general simulation platform for seaport container terminals, Advanced Engineering Informatics, 26(1), 80-89.Trappey, C. V., Lin, G. Y., Trappey, A. J., Liu, C. S., and Lee, W. T. (2011), Deriving industrial logistics hub reference models for manufacturing based economies, Expert Systems with Applications, 38(2), 1223-1232.Wang, S. and Meng, Q. (2012), Liner ship route schedule design with sea contingency time and port time uncertainty, Transportation Research Part B: Methodological, 46(5), 615-633.Wang, S., Alharbi, A., and Davy, P. (2014), Liner ship route schedule design with port time windows, Transportation Research Part C: Emerging Technologies, 41, 1-17.Wang, S., Alharbi, A., and Davy, P. (2015), Ship route schedule based interactions between container shipping lines and port operators. In: C.-Y. Lee, Q. Meng (Eds.), Handbook of Ocean Container Transport Logistics: Making Global Supply Chains Effective, International Series in Operations Research & Management Science, Elsevier, Vol. 220, 279-313, Available from: http://dx.doi.org/10.1007/978-3-319 -11891-8_10.Yan, S., Chen, C.-Y., and Lin, S.-C. (2009), Ship scheduling and container shipment planning for liners in short-term operations, Journal of Marine Science and Technology, 14(4), 417-435.Yin, X. F., Khoo, L. P., and Chen, C.- H. (2011), A distributed agent system for port planning and scheduling, Advanced Engineering Informatics, 25(3), 403-412.671662420Transport network transport network designContainer supply chainLine schedulingGenetic algorithmPublicationORIGINALScheduling for a container supply chain to minimize costs using the meta-innovation approach.pdfScheduling for a container supply chain to minimize costs using the meta-innovation approach.pdfapplication/pdf448888https://repositorio.cuc.edu.co/bitstreams/4f2d69be-4199-4147-970d-12750ecaa311/downloadaecc1de5b34f3224c9a3a80bd1309cbeMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstreams/370a5cfd-c85e-4416-9bb0-629bd3857c51/downloade30e9215131d99561d40d6b0abbe9badMD52TEXTScheduling for a container supply chain to minimize costs using the meta-innovation approach.pdf.txtScheduling for a container supply chain to minimize costs using the meta-innovation 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