Abstract
The most important factors to consider in transportation are the items being transported, the origin and destination locations, the length of the trip, the mode of transportation required (truck, train, plane, or ship), the shipping due dates, the costs, the level of security, regulation, and monitoring, and the costs. Specifically, the goal of this study is to determine the cost of, delivery time for, and greenhouse gas (GHG) emissions related to the import of less than container load (LCL) from China to Pakistan. For the multiobjective problem, we employed the mixed-integer linear programming (MILP) approach to construct it while keeping the supply and demand constraints in mind. We tackled the problem using a multiobjective evolutionary algorithm and developed Pareto optimal solutions that could trade-off cost, time, and GHG emission in order to achieve the best possible result. According to the data, which was received from one of Pakistan’s top logistics service companies, using intermodal transportation to carry a ten-tonne product from Shanghai in China to Kasur in Pakistan will cost 37 per cent more, take 14 per cent longer, and emit more greenhouse gases than using traditional multimodal transportation.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aldana H, Lozano FJ, Acevedo J (2014) Evaluating the potential for producing energy from agricultural residues in México using MILP optimization. Biomass Bioenerg 67:372–389. https://doi.org/10.1016/j.biombioe.2014.05.022
Aviso KB, Tan RR, Culaba AB, Cruz JB (2010) Bi-level fuzzy optimization approach for water exchange in eco-industrial parks. Process Saf Environ Prot 88:31–40. https://doi.org/10.1016/J.PSEP.2009.11.003
Ayar B, Yaman H (2012) An intermodal multicommodity routing problem with scheduled services. Comput Optim Appl 53:131–153. https://doi.org/10.1007/s10589-011-9409-z
Bixby RE (2012) A brief history of linear and mixed-integer programming computation. Doc math extra ISMP ISMP:107–121
Bontekoning YM, Macharis C, Trip JJ (2004) Is a new applied transportation research field emerging? - A review of intermodal rail-truck freight transport literature. Transp Res Part A Policy Pract 38:1–34. https://doi.org/10.1016/j.tra.2003.06.001
Chang Z, Weng J, Qi Z, Yang D (2019) Assess economic and environmental trade-off for inland port location. Int J Shipp Transp Logist 11:243–261. https://doi.org/10.1504/IJSTL.2019.099277
Cho JH, Soo H, Hyung K et al (2010) An intermodal transport network planning algorithm using dynamic programming—A case study: from Busan to Rotterdam in intermodal freight routing. Appl Intell 36:529–541. https://doi.org/10.1007/S10489-010-0223-6
Craig AJ, Blanco EE, Sheffi Y (2013) Estimating the CO2 intensity of intermodal freight transportation. Transp Res Part D Transp Environ 22:49–53. https://doi.org/10.1016/j.trd.2013.02.016
DBEIS (2021) Government conversion factors for company reporting of greenhouse gas emissions. https://www.gov.uk/government/collections/government-conversion-factors-for-company-reporting. Accessed 3 Nov 2022
Demir E, Burgholzer W, Hrušovský M et al (2016) A green intermodal service network design problem with travel time uncertainty. Transp Res Part B Methodol 93:789–807. https://doi.org/10.1016/j.trb.2015.09.007
Geerlings H, Van Duin R (2011) A new method for assessing CO2-emissions from container terminals: a promising approach applied in Rotterdam. J Clean Prod 19:657–666. https://doi.org/10.1016/j.jclepro.2010.10.012
Gialos A, Zeimpekis V, Madas M, Papageorgiou K (2022) Calculation and assessment of CO2e emissions in road freight transportation: a Greek case study. Sustain 14:10724. https://doi.org/10.3390/su141710724
Government of Pakistan (2020) Economic survey. Economic Advisor’s Wing, Ministry of Finance, Islamabad
Hannah Ritchie MR (2021) Pakistan: Per capita: how much CO2 does the average person emit? In: our world data. https://ourworldindata.org/co2/country/pakistan. Accessed 3 Dec 2021
Helmers E, Leitão J, Tietge U, Butler T (2019) CO2-equivalent emissions from European passenger vehicles in the years 1995–2015 based on real-world use: assessing the climate benefit of the European “diesel boom.” Atmos Environ 198:122–132. https://doi.org/10.1016/j.atmosenv.2018.10.039
Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. Univ Michigan Press, Ann Arbor, p 183
International Energy Agency (2018) Global Energy and CO2 Status Report. IEA Publications, Paris, France
Kantor I, Robineau JL, Bütün H, Maréchal F (2020) A mixed-integer linear programming formulation for optimizing multi-scale material and energy integration. Front Energy Res 8:49. https://doi.org/10.3389/FENRG.2020.00049/BIBTEXA
Kelechi O, Tokos H (2016) An MILP model for the optimization of hybrid renewable energy system. In: computer aided chemical engineering. Elsevier, Amsterdam, pp 2193–2198
Lam JSL, Gu Y (2013) Port hinterland intermodal container flow optimisation with green concerns: a literature review and research agenda. Int J Shipp Transp Logist 5:257–281. https://doi.org/10.1504/IJSTL.2013.054190
Lam JJSL, Gu Y (2016) A market-oriented approach for intermodal network optimisation meeting cost, time and environmental requirements. Int J Prod Econ 171:266–274. https://doi.org/10.1016/j.ijpe.2015.09.024
Liu Z, Meng Q, Wang S et al (2014) Global intermodal liner shipping network design. Elsevier, Amsterdam
Lv Q, Liu H, Yang D, Liu H (2019) Effects of urbanization on freight transport carbon emissions in China: common characteristics and regional disparity. J Clean Prod 211:481–489. https://doi.org/10.1016/J.JCLEPRO.2018.11.182
Macharis C, Caris A, Jourquin B, Pekin E (2011) A decision support framework for intermodal transport policy. Eur Transp Res Rev 3:167–178. https://doi.org/10.1007/S12544-011-0062-5
Macharis C, Bontekoning YM (2004) Opportunities for OR in intermodal freight transport research: a review. Eur J Oper Res 153:400–416. https://doi.org/10.1016/S0377-2217(03)00161-9
Madankumar S, Rajendran C (2018) Mathematical models for green vehicle routing problems with pickup and delivery: a case of semiconductor supply chain. Comput Oper Res 89:183–192. https://doi.org/10.1016/j.cor.2016.03.013
Mahadevan K, Bäumler I, Kotzab H (2021) Frame conditions, mindsets and skills in supply chain management from Taylorism to industry 4.0. World Rev Intermodal Transp Res 10:305–324. https://doi.org/10.1504/WRITR.2021.119534
Malik S (2012) The structure and behavior of Pakistan ‘ s Imports from selected Asian Countries : an application of. Econstor Eu 6:53–66
Mathisen TA, Hanssen TES (2014) The academic literature on intermodal freight transport. Transp Res Procedia. 3:611–620
Nguyen P, Durden GR, Nguyen PTT et al (2008) Organizational logistics processes: A literature review and an exploratory investigation of international multimodal transport in Vietnam. Asia Pacific Manag Rev. 13:403–418
Pakistan Bureau of Statistics G of P (2021) Imports of Pakistan. https://www.pbs.gov.pk/. Accessed 3 Nov 2022
Pallme D, Lambert B, Miller C, Lipinski M (2015) A review of public and private intermodal railroad development in the Memphis region. Res Transp Bus Manag 14:44–55. https://doi.org/10.1016/j.rtbm.2014.10.011
Resat HG, Turkay M (2015) Design and operation of intermodal transportation network in the Marmara region of Turkey. Transp Res Part E Logist Transp Rev 83:16–33. https://doi.org/10.1016/j.tre.2015.08.006
Resat HG, Turkay M (2019) A bi-objective model for design and analysis of sustainable intermodal transportation systems: a case study of Turkey. Int J Prod Res 57:6146–6161. https://doi.org/10.1080/00207543.2019.1587187
Santos-Paulino A, Thirlwall AP (2004) The impact of trade liberalisation on exports, imports and the balance of payments of developing countries. Econ J. https://doi.org/10.1111/j.0013-0133.2004.00187.x
Shoukat R (2021) Modelling and analysis of intermodal freight cost and CO2emissions: Application of mixed-integer linear programming and genetic algorithm. World Rev Intermodal Transp Res 10:378–399. https://doi.org/10.1504/WRITR.2021.119532
Sun Y, Lang M (2015) Modeling the multicommodity multimodal routing problem with schedule-based services and carbon dioxide emission costs. Math Probl Eng. https://doi.org/10.1155/2015/406218
Wang Q, Wang S (2019) A comparison of decomposition the decoupling carbon emissions from economic growth in transport sector of selected provinces in eastern, central and western China. J Clean Prod 229:570–581. https://doi.org/10.1016/J.JCLEPRO.2019.04.375
Wang J, Lim MK, Tseng ML, Yang Y (2019) Promoting low carbon agenda in the urban logistics network distribution system. J Clean Prod 211:146–160. https://doi.org/10.1016/J.JCLEPRO.2018.11.123
Yang X, Low JMW, Tang LC (2011) Analysis of intermodal freight from China to Indian Ocean: A goal programming approach. J Transp Geogr 19:515–527. https://doi.org/10.1016/J.JTRANGEO.2010.05.007
Zhang D, He R, Li S, Wang Z (2017) A multimodal logistics service network design with time windows and environmental concerns. PLoS ONE 12:e0185001. https://doi.org/10.1371/JOURNAL.PONE.0185001
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
No potential conflict of interest was reported by the authors.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Shoukat, R. Multimodal or intermodal: greenhouse gas emissions in less than container load in China–Pakistan trade. Environ Syst Decis 43, 265–280 (2023). https://doi.org/10.1007/s10669-022-09887-7
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10669-022-09887-7