Abstract
The case studies are introduced in this study, highlighting freight transportation via road and road rail between satellite cities in Pakistan’s Punjab and Sindh provinces. The case study analysis contributes to developing environmentally friendly and cost-effective transportation solutions and reducing nitrous oxide (N2O) and carbon dioxide (CO2) emissions associated with road and intermodal freight transit. We developed a mixed-integer linear programming (MILP) model to formulate the bi-objective problem, including real-life constraints, emissions at starting nodes, ending notes, and between the arc. In the mathematical model, the cost and emissions functions are developed to minimize the primary and secondary objective functions in the road and intermodal transportation. Furthermore, five distinct sets (locations, starting stations, ending stations, transport orders, and transport service) with parameters relating to container movement between the starting and ending nodes are a necessary part of the MILP formulation. The multiobjective optimization problem is solved by metaheuristic techniques such as the multiobjective genetic algorithm as the goal of applying a metaheuristic algorithm is to find the search space to search the near to optimized solutions. The Pareto front solutions are provided for balancing the costs and emissions of transporting supplies from Punjab to Sindh using the MATLAB solver toolbox. We gathered data from one of Pakistan’s most well-known logistics service providers in the paper industry. According to the findings, intermodal transportation is 72% more cost-effective than road transportation. Additionally, by substituting intermodal transportation for road transportation, N2O, and CO2 emissions can be reduced by 74% and 57%, respectively.
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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
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
Bakhsh K, Rose S, Ali MF et al (2017) Economic growth, CO2 emissions, renewable waste and FDI relation in Pakistan: new evidences from 3SLS. J Environ Manage 196:627–632. https://doi.org/10.1016/j.jenvman.2017.03.029
Bask A, Rajahonka M (2017) The role of environmental sustainability in the freight transport mode choice. Int J Phys Distrib Logist Manag 47:560–602. https://doi.org/10.1108/ijpdlm-03-2017-0127
Bixby RE (2012) A brief history of linear and mixed-integer programming computation. Doc Math Extra ISMP ISMP 107–121
Chien F, Hsu CC, Ozturk I et al (2022) The role of renewable energy and urbanization towards greenhouse gas emission in top Asian countries: evidence from advance panel estimations. Renew Energy 186:207–216. https://doi.org/10.1016/j.renene.2021.12.118
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 (2023) Government conversion factors for company reporting of greenhouse gas emissions. https://www.gov.uk/government/collections/government-conversion-factors-for-company-reporting
Demir E, Hrušovský M, Jammernegg W, Van Woensel T (2019) Green intermodal freight transportation: bi-objective modelling and analysis. Int J Prod Res 57:6162–6180. https://doi.org/10.1080/00207543.2019.1620363
Department for Business Energy & Industrial Strategy (2020) Greenhouse gas reporting: conversion factors, UK
Eiben AE, Raué PE, Ruttkay Z (1994) Genetic algorithms with multi-parent recombination. In: Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics). Springer Verlag, pp 78–87
EPA (2021) Overview of greenhouse gases. https://www.epa.gov/ghgemissions/overview-greenhouse-gases
Garcia-Alvarez A, Perez-Martinez PJ, Gonzalez-Franco I (2013) Energy consumption and carbon dioxide emissions in rail and road freight transport in Spain: a case study of car carriers and bulk petrochemicals. J Intell Transp Syst Technol Plann Oper 17:233–244. https://doi.org/10.1080/15472450.2012.719456
Government of Pakistan (2020) Economic survey. Economic Advisor’s Wing, Ministry of Finance, Islamabad
Habib-ur-Rehman (2009) Pakistan economic survey, Government of Pakistan, Finance Division
Holguín-Veras J, Wojtowicz J (2012) Freight transportation cost data element. Transportation Research Board
Holland JH (1975) Adaptation in natural and artificial systems : an introductory analysis with applications to biology, control, and artificial intelligence. Ann Arbor Univ Michigan Press 1975 viii, p 183
Homayouni SM, Fontes DBMM (2021) A MILP model for energy-efficient job shop scheduling problem and transport resources. In: IFIP advances in information and communication technology. Springer Science and Business Media Deutschland GmbH, pp 378–386
Izadi A, Nabipour M, Titidezh O (2020) Cost models and cost factors of road freight transportation: a literature review and model structure. Fuzzy Inf Eng 00:1–21. https://doi.org/10.1080/16168658.2019.1688956
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, pp 2193–2198
Kim M, Kim MJ, Pyo SH et al (2016) Greenhouse emission pinch analysis (GEPA) for evaluation of emission reduction strategies. Clean Technol Environ Policy 18:1381–1389. https://doi.org/10.1007/s10098-015-1063-1
Kurtuluş E, Çetin İB (2020) Analysis of modal shift potential towards intermodal transportation in short-distance inland container transport. Transp Policy 89:24–37. https://doi.org/10.1016/j.tranpol.2020.01.017
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
Mitchell M (1998) An introduction to genetic algorithms. MIT Press
Nelldal B-L, Andersson E (2012) Mode shift as a measure to reduce greenhouse gas emissions. Procedia Soc Behav Sci 48:3187–3197. https://doi.org/10.1016/j.sbspro.2012.06.1285
Ramanathan R (2001) The long-run behavior of transport performance in India: a cointegration approach. Transp Res Part A Policy Pract 35:309–320. https://doi.org/10.1016/S0965-8564(99)00060-9
Raza MY, Lin B (2020) Decoupling and mitigation potential analysis of CO2 emissions from Pakistan’s transport sector. Sci Total Environ 730:139000. https://doi.org/10.1016/j.scitotenv.2020.139000
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
Saeed A, Zhang X, Shoukat R (2023) United Arab Emirates-Pakistan: the role of rail in green and economical intermodal and multimodal. Int J Shipp Transp Logist 1:1. https://doi.org/10.1504/ijstl.2023.10048002
Shen S, Fowkes T, Whiteing T, Johnson D (2009) Econometric modelling and forecasting of freight transport demand in Great Britain. Eur Transp 1–21
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
Shoukat R, Xiaoqiang Z (2022) Sustainable logistics network optimization from dry ports to seaport: a case study from Pakistan. Transp Res Rec J Transp Res Board. https://doi.org/10.1177/03611981221115121
Shoukat R, Zhang X (2022) A bi-objective approach to minimise cost and CO<SUB align="right">2 emissions in intermodal freight transport for biomass energy. Int J Shipp Transp Logist 15:329. https://doi.org/10.1504/ijstl.2022.10051954
Walmsley MRW, Walmsley TG, Atkins MJ et al (2015) carbon emissions pinch analysis for emissions reductions in the New Zealand transport sector through to 2050. Energy. https://doi.org/10.1016/j.energy.2015.04.069
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Shoukat, R., Xiaoqiang, Z. How the paper industry is devastating Pakistani environment: an application of the MILP and MOGA. Int. J. Environ. Sci. Technol. 21, 1889–1904 (2024). https://doi.org/10.1007/s13762-023-05073-7
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DOI: https://doi.org/10.1007/s13762-023-05073-7