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Sustainability-based review of urban freight models

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Abstract

This paper provides a review of models and decision support systems for urban freight transport (UFT). The originality of this study is that the analysis framework has been developed to outline the progress on UFT specifically related to the sustainability issue. Accordingly, contributions regarding UFT and addressing at least one factor of sustainability have been analysed by cross-referencing categories of models with impacts on sustainability. Results from this work are supposed to help enhance research concerning operations research (OR) for sustainable UFT by pointing out gaps that need to be closed and opportunities for future research. There is also an attempt to understand what is stopping researchers from including selected sustainability factors in the optimisation models. This paper also finally proposes some developments, not only in the OR field, that are preparatory for elaborating new models or improving the existing ones.

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References

  • Allen J, Thorne G, Browne M (2007) BESTUFS good practice guide on urban freight transport. In: Good practice guide on urban freight transport. BESTUFS EU Thematic Network, Brussels

  • Allen J, Browne M, Holguin-Veras J (2010) Sustainability strategies for city logistics. Improving the environmental sustainability of logistics, Green Logist, pp 282–305

    Google Scholar 

  • Alumur SA, Kara BY, Karasan OE (2012) Multimodal hub location and hub network design. Omega 40(6):927–939

    Article  Google Scholar 

  • Ambrosini C, Routhier JL (2004) Objectives, methods and results of surveys carried out in the field of urban freight transport: an international comparison. Transport Rev 24(1):57–77

    Article  Google Scholar 

  • Ambrosini C, Routhier JL, Sonntag H, Meimbresse B (2008) Urban freight modelling: a review. In: Taniguchi E, Thompson RG (eds) Innovations in City Logistics, Nova Science Publishers, New York, pp 197–211

    Google Scholar 

  • Ameknassi L, Aït-Kadi D, Rezg N (2016) Integration of logistics outsourcing decisions in a green supply chain design: a stochastic multi-objective multi-period multi-product programming model. Int J Prod Econ 182:165–184

    Article  Google Scholar 

  • Andersen J, Crainic TG, Christiansen M (2009) Service network design with management and coordination of multiple fleets. Eur J Oper Res 193(2):377–389

    Article  MathSciNet  MATH  Google Scholar 

  • Arampantzi C, Minis I (2017) A new model for designing sustainable supply chain networks and its application to a global manufacturer. J Clean Prod 156:276–292

    Article  Google Scholar 

  • AustriaTech (2014) Annex: electric fleets in urban logistics—overview of current low emission vehicles. Published as part of the ENCLOSE project. http://www.austriatech.at/files/get/9e26eb124ad90ffa93067085721d4942/austriatech_electricfleets_annex.pdf. Last accessed 22 May 2014

  • Awasthi A, Chauhan SS, Goyal SK (2011) A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty. Math Comput Model 53(1–2):98–109

    Article  MathSciNet  MATH  Google Scholar 

  • Ayar B, Yaman H (2012) An intermodal multicommodity routing problem with scheduled services. Comput Optim Appl 53(1):131–153

    Article  MathSciNet  MATH  Google Scholar 

  • Babazadeh R, Razmi J, Pishvaee MS, Rabbani M (2017) A sustainable second-generation biodiesel supply chain network design problem under risk. Omega 66:258–277

    Article  Google Scholar 

  • Bandeira DL, Becker JL, Borenstein D (2009) A DSS for integrated distribution of empty and full containers. Decis Support Syst 47(4):383–397

    Article  Google Scholar 

  • Barceló J, Grzybowska H, Pardo S (2007) Vehicle routing and scheduling models, simulation and city logistics. In: Zeimpekis V, Tarantilis CD, Giaglis GM, Minis I (eds) Dynamic fleet management. Springer, Boston, MA, pp 163–195

    Chapter  Google Scholar 

  • Behrends S (2011) Urban freight transport sustainability-the interaction of urban freight and intermodal transport. Chalmers University of Technology, Gothenburg

    Google Scholar 

  • Behrends S, Lindholm M, Woxenius J (2008) The impact of urban freight transport: a definition of sustainability from an actor’s perspective. Transp Plan Technol 31(6):693–713

    Article  Google Scholar 

  • Bektaş T, Laporte G (2011) The pollution-routing problem. Transp Res B Methodol 45(8):1232–1250

    Article  Google Scholar 

  • Bielli M, Bielli A, Rossi R (2011) Trends in models and algorithms for fleet management. Procedia Soc Behav Sci 20:4–18

    Article  Google Scholar 

  • Bock S (2010) Real-time control of freight forwarder transportation networks by integrating multimodal transport chains. Eur J Oper Res 200(3):733–746

    Article  MathSciNet  MATH  Google Scholar 

  • 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 A Policy Pract 38(1):1–34

    Article  Google Scholar 

  • Boonsothonsatit K, Kara S, Ibbotson S, Kayis B (2015) Development of a generic decision support system based on multi-objective optimization for green supply chain network design (GOOG). J Manuf Technol Manag 26(7):1069–1084

    Article  Google Scholar 

  • Boschian V, Paganelli P, Pondrelli L (2013) A global freight business ecosystem based on low carbon end-to-end transport and logistic services. Int J Adv Logist 2(1):1–14

    Article  Google Scholar 

  • Brandenburg M (2015) Low carbon supply chain configuration for a new product—a goal programming approach. Int J Prod Res 53(21):6588–6610

    Article  Google Scholar 

  • Bravo JJ, Vidal CJ (2013) Freight transportation function in supply chain optimization models: a critical review of recent trends. Expert Syst Appl 40(17):6742–6757

    Article  Google Scholar 

  • Brown JR, Guiffrida AL (2014) Carbon emissions comparison of last mile delivery versus customer pickup. Int J Logist Res Appl 17(6):503–521

    Article  Google Scholar 

  • Browne M, Piotrowska M, Woodburn A, Allen J (2007) Literature review WM9: part I-urban freight transport. Green logistics project. University of Westminster, London

    Google Scholar 

  • Browne M, Allen J, Nemoto T, Patier D, Visser J (2012) Reducing social and environmental impacts of urban freight transport: a review of some major cities. Procedia Soc Behav Sci 39:19–33

    Article  Google Scholar 

  • Brundtland GH (1985) World commission on environment and development. Environ Policy Law 14(1):26–30

    Google Scholar 

  • Brundtland GH (1987) What is sustainable development. In: Our common future. Report of the 1987 World Commission on Environment and Development, pp 8–9

  • Buldeo Rai H, van Lier T, Meers D, Macharis C (2018) An indicator approach to sustainable urban freight transport. J Urban Int Res Placemak Urban Sustain 11(1):81–102

    Article  Google Scholar 

  • Cachon GP (2014) Retail store density and the cost of greenhouse gas emissions. Manag Sci 60(8):1907–1925

    Article  Google Scholar 

  • Chen X, Wang X (2016) Effects of carbon emission reduction policies on transportation mode selections with stochastic demand. Transp Res E Logist Transp Rev 90:196–205

    Article  Google Scholar 

  • Chen D, Ignatius J, Sun D, Goh M, Zhan S (2018) Impact of congestion pricing schemes on emissions and temporal shift of freight transport. Transp Res E Logist Transp Rev 118:77–105

    Article  Google Scholar 

  • Comi A, Donnelly R, Russo F (2014) Urban freight models. In: Tavasszy L, De Jong J (eds) Modelling freight transport, chap 8, Elsevier, pp 163–200. https://doi.org/10.1016/B978-0-12-410400-6.00008-2

  • Danloup N, Mirzabeiki V, Allaoui H, Goncalves G, Julien D, Mena C (2015) Reducing transportation greenhouse gas emissions with collaborative distribution a case study. Manag Res Rev 38(10):1049–1067

    Article  Google Scholar 

  • Dehghanian F, Mansour S (2009) Designing sustainable recovery network of end-of-life products using genetic algorithm. Resour Conserv Recycl 53(10):559–570

    Article  Google Scholar 

  • Demir E, Bektaş T, Laporte G (2012) An adaptive large neighborhood search heuristic for the pollution-routing problem. Eur J Oper Res 223(2):346–359

    Article  MathSciNet  MATH  Google Scholar 

  • Demir E, Bektaş T, Laporte G (2014) A review of recent research on green road freight transportation. Eur J Oper Res 237(3):775–793

    Article  MATH  Google Scholar 

  • Devika K, Jafarian A, Nourbakhsh V (2014) Designing a sustainable closed-loop supply chain network based on triple bottom line approach: a comparison of metaheuristics hybridization techniques. Eur J Oper Res 235(3):594–615

    Article  MathSciNet  MATH  Google Scholar 

  • E-commerce Statistics for Individuals (2018) Statistics Explained. Retrieved from http://ec.europa.eu/eurostat/statisticsexplained/. Accessed 14 May 2018

  • Elhedhli S, Merrick R (2012) Green supply chain network design to reduce carbon emissions. Transp Res D Transport Environ 17(5):370–379

    Article  Google Scholar 

  • Elhedhli S, Wu H (2010) A Lagrangean heuristic for hub-and-spoke system design with capacity selection and congestion. INFORMS J Comput 22(2):282–296

    Article  MathSciNet  MATH  Google Scholar 

  • Elkington J (1997) Cannibals with forks: the triple bottom line of twentieth century business. Capstone, Oxford

    Google Scholar 

  • Farahani RZ, Hekmatfar M, Arabani AB, Nikbakhsh E (2013) Hub location problems: a review of models, classification, solution techniques, and applications. Comput Ind Eng 64(4):1096–1109

    Article  Google Scholar 

  • Fareeduddin M, Hassan A, Syed MN, Selim SZ (2015) The impact of carbon policies on closed-loop supply chain network design. Procedia CIRP 26:335–340

    Article  Google Scholar 

  • Fathollahi-Fard AM, Hajiaghaei-Keshteli M, Mirjalili S (2018) Multi-objective stochastic closed-loop supply chain network design with social considerations. Appl Soft Comput 71:505–525

    Article  Google Scholar 

  • Faulin J, Juan A, Lera F, Grasman S (2011) Solving the capacitated vehicle routing problem with environmental criteria based on real estimations in road transportation: a case study. Procedia Soc Behav Sci 20:323–334

    Article  Google Scholar 

  • Figliozzi MA (2011) The impacts of congestion on time-definitive urban freight distribution networks CO2 emission levels: results from a case study in Portland, Oregon. Transp Res C Emerging Technol 19(5):766–778

    Article  Google Scholar 

  • Franceschetti A, Honhon D, Van Woensel T, Bektaş T, Laporte G (2013) The time-dependent pollution-routing problem. Transp Res B Methodol 56:265–293

    Article  Google Scholar 

  • Friedrich M, Haupt T, Nökel K (2003, August) Freight modelling: data issues, survey methods, demand and network models. In: 10th international conference on travel behaviour research, Lucerne, Switzerland, August

  • Glock CH, Kim T (2015) Coordinating a supply chain with a heterogeneous vehicle fleet under greenhouse gas emissions. Int J Logist Manag 26(3):494–516

    Article  Google Scholar 

  • Govindan K, Darbari JD, Agarwal V, Jha PC (2017) Fuzzy multi-objective approach for optimal selection of suppliers and transportation decisions in an eco-efficient closed loop supply chain network. J Clean Prod 165:1598–1619

    Article  Google Scholar 

  • Hammad AW, Akbarnezhad A, Rey D (2017) Sustainable urban facility location: minimising noise pollution and network congestion. Transp Res E Logist Transp Rev 107:38–59

    Article  Google Scholar 

  • Hoen KMR, Tan T, Fransoo JC, Van Houtum GJ (2013) Switching transport modes to meet voluntary carbon emission targets. Transp Sci 48(4):592–608

    Article  Google Scholar 

  • Hoen KMR, Tan T, Fransoo JC, Van Houtum GJ (2014) Effect of carbon emission regulations on transport mode selection under stochastic demand. Flex Serv Manuf J 26(1–2):170–195

    Article  Google Scholar 

  • Hu J, Morais H, Sousa T, Lind M (2016) Electric vehicle fleet management in smart grids: a review of services, optimization and control aspects. Renew Sustain Energy Rev 56:1207–1226

    Article  Google Scholar 

  • Ishfaq R, Sox CR (2010) Intermodal logistics: the interplay of financial, operational and service issues. Transp Res E Logist Transp Rev 46(6):926–949

    Article  Google Scholar 

  • Ishfaq R, Sox CR (2011) Hub location–allocation in intermodal logistic networks. Eur J Oper Res 210(2):213–230

    Article  MathSciNet  MATH  Google Scholar 

  • Ishfaq R, Sox CR (2012) Design of intermodal logistics networks with hub delays. Eur J Oper Res 220(3):629–641

    Article  MathSciNet  MATH  Google Scholar 

  • Jabali O, Van Woensel T, De Kok AG (2012) Analysis of travel times and CO2 emissions in time-dependent vehicle routing. Prod Oper Manag 21(6):1060–1074

    Article  Google Scholar 

  • Jakovljevic B, Paunovic K, Belojevic G (2009) Road-traffic noise and factors influencing noise annoyance in an urban population. Environ Int 35(3):552–556

    Article  Google Scholar 

  • Junior O, Duffrayer PA (2017) Evaluating the economical and environmental impact of a cargo cycle urban distribution: a case study. Doctoral dissertation

  • Kang J (2006) Urban sound environment. CRC Press, Boca Raton

    Book  Google Scholar 

  • Kannan D, Diabat A, Alrefaei M, Govindan K, Yong G (2012) A carbon footprint based reverse logistics network design model. Resour Conserv Recycl 67:75–79

    Article  Google Scholar 

  • Kumar RS, Kondapaneni K, Dixit V, Goswami A, Thakur LS, Tiwari MK (2016) Multi-objective modeling of production and pollution routing problem with time window: a self-learning particle swarm optimization approach. Comput Ind Eng 99:29–40

    Article  Google Scholar 

  • Kwon YJ, Choi YJ, Lee DH (2013) Heterogeneous fixed fleet vehicle routing considering carbon emission. Transp Res D Transport Environ 23:81–89

    Article  Google Scholar 

  • Lam HL, Varbanov PS, Klemes JJ (2010) Optimization of regional energy supply chains utilizing renewables: P-graph approach. Comput Chem Eng 34(5):782–792

    Article  Google Scholar 

  • Li J, Su Q, Ma L (2017) Production and transportation outsourcing decisions in the supply chain under single and multiple carbon policies. J Clean Prod 141:1109–1122

    Article  Google Scholar 

  • Liljestrand K, Christopher M, Andersson D (2015) Using a transport portfolio framework to reduce carbon footprint. Int J Logist Manag 26(2):296–312

    Article  Google Scholar 

  • Limbourg S, Jourquin B (2009) Optimal rail-road container terminal locations on the European network. Transp Res E Logist Transp Rev 45(4):551–563

    Article  Google Scholar 

  • Lindholm M, Behrends S (2012) Challenges in urban freight transport planning—a review in the Baltic Sea Region. J Transp Geogr 22:129–136

    Article  Google Scholar 

  • Loni P, Khamseh AA, Pasandideh SHR (2018) A new multi-objective/product green supply chain considering quality level reprocessing cost. Int J Serv Oper Manag 30(1):1–22

    Google Scholar 

  • Macharis C, Bontekoning YM (2004) Opportunities for OR in intermodal freight transport research: a review. Eur J Oper Res 153(2):400–416

    Article  MATH  Google Scholar 

  • Maden W, Eglese R, Black D (2010) Vehicle routing and scheduling with time-varying data: a case study. J Oper Res Soc 61(3):515–522

    Article  MATH  Google Scholar 

  • Manzini R, Bindi F (2009) Strategic design and operational management optimization of a multi stage physical distribution system. Transp Res E Logist Transp Rev 45(6):915–936

    Article  Google Scholar 

  • MDS Transmodal (2012) Study on urban freight transport, for DG MOVE, European Commission. Retrieved from http://ec.europa.eu/transport/themes/urban/studies/doc/2012-04-urban-freight-transport.pdf. Accessed 9 May 2018

  • Mohajeri A, Fallah M (2014) Closed-loop supply chain models with considering the environmental impact. Sci World J 2014:852529. https://doi.org/10.1155/2014/852529

    Article  Google Scholar 

  • Mohajeri A, Fallah M (2014b) Cost minimization model for reducing carbon footprints from different transportation modes. Int J Appl 4(4):49–76

    Google Scholar 

  • Mohajeri A, Fallah M (2016) A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: a case study. Transp Res D Transport Environ 48:425–450

    Article  Google Scholar 

  • Mohammed F, Selim SZ, Hassan A, Syed MN (2017) Multi-period planning of closed-loop supply chain with carbon policies under uncertainty. Transp Res D Transport Environ 51:146–172

    Article  Google Scholar 

  • Monteiro MM, Leal JE, Raupp FMP (2010) A four-type decision-variable MINLP model for a supply chain network design. Math Probl Eng 2010:1–16

    Article  MATH  Google Scholar 

  • Musavi MM, Bozorgi-Amiri A (2017) A multi-objective sustainable hub location-scheduling problem for perishable food supply chain. Comput Ind Eng 113:766–778

    Article  Google Scholar 

  • Nightingale A (2009) A guide to systematic literature reviews. Surgery (Oxford) 27(9):381–384

    Article  Google Scholar 

  • Nouira I, Hammami R, Frein Y, Temponi C (2016) Design of forward supply chains: impact of a carbon emissions-sensitive demand. Int J Prod Econ 173:80–98

    Article  Google Scholar 

  • Oberscheider M, Zazgornik J, Henriksen CB, Gronalt M, Hirsch P (2013) Minimizing driving times and greenhouse gas emissions in timber transport with a near-exact solution approach. Scand J For Res 28(5):493–506

    Article  Google Scholar 

  • Ogden KW (1992) Urban goods movement: a guide to policy and planning. Ashgate, Hants, England

    Google Scholar 

  • Paksoy T, Bektaş T, Özceylan E (2011) Operational and environmental performance measures in a multi-product closed-loop supply chain. Transp Res E Logist Transp Rev 47(4):532–546

    Article  Google Scholar 

  • Passchier-Vermeer W, Passchier WF (2000) Noise exposure and public health. Environ Health Perspect 108(suppl 1):123–131

    Article  Google Scholar 

  • Pishvaee MS, Razmi J, Torabi SA (2012a) Robust possibilistic programming for socially responsible supply chain network design: a new approach. Fuzzy Sets Syst 206:1–20

    Article  MathSciNet  MATH  Google Scholar 

  • Pishvaee MS, Torabi SA, Razmi J (2012b) Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty. Comput Ind Eng 62:624–632

    Article  Google Scholar 

  • Pradenas L, Oportus B, Parada V (2013) Mitigation of greenhouse gas emissions in vehicle routing problems with backhauling. Expert Syst Appl 40(8):2985–2991

    Article  Google Scholar 

  • Puettmann C, Stadtler H (2010) A collaborative planning approach for intermodal freight transportation. OR Spectrum 32(3):809–830

    Article  MATH  Google Scholar 

  • Qiu Y, Qiao J, Pardalos PM (2017) A branch-and-price algorithm for production routing problems with carbon cap-and-trade. Omega 68:49–61

    Article  Google Scholar 

  • Quak H (2008) Sustainability of urban freight transport: retail distribution and local regulations in cities (No. EPS-2008-124-LIS)

  • Quak H (2011) Urban freight transport: the challenge of sustainability. In: Macharis C, Melo S (eds) City distribution and urban freight transport: multiple perspectives. Edward Elgar Publishing, pp 37–55

  • Ranieri L, Digiesi S, Silvestri B, Roccotelli M (2018) A review of last mile logistics innovations in an externalities cost reduction vision. Sustainability 10(3):782

    Article  Google Scholar 

  • Rao C, Goh M, Zhao Y, Zheng J (2015) Location selection of city logistics centers under sustainability. Transp Res D 36:29–44

    Article  Google Scholar 

  • Richardson BC (2005) Sustainable transport: analysis frameworks. J Transp Geogr 13(1):29–39

    Article  Google Scholar 

  • Rudi A, Frohling M, Zimmer K, Schultmann F (2016) Freight transportation planning considering carbon emissions and in-transit holding costs: a capacitated multi-commodity network flow model. EURO J Transp Logist 5(2):123–160

    Article  Google Scholar 

  • Saberi M, Verbas İÖ (2012) Continuous approximation model for the vehicle routing problem for emissions minimization at the strategic level. J Transp Eng 138(11):1368–1376

    Article  Google Scholar 

  • Sadegheih A, Drake PR, Li D, Sribenjachot S (2011) Global supply chain management under the carbon emission trading program using mixed integer programming and genetic algorithm. Int J Eng Trans B 24(1):37–53

    Google Scholar 

  • Sadjady H, Davoudpour H (2012) Two-echelon, multi-commodity supply chain network design with mode selection, lead-times and inventory costs. Comput Oper Res 39(7):1345–1354

    Article  MathSciNet  MATH  Google Scholar 

  • Sahebjamnia N, Fard AMF, Hajiaghaei-Keshteli M (2018) Sustainable tire closed-loop supply chain network design: hybrid metaheuristic algorithms for large-scale networks. J Clean Prod 196:273–296

    Article  Google Scholar 

  • Seuring S, Sarkis J, Müller M, Rao P (2008) Sustainability and supply chain management—an introduction to the special issue. J Clean Prod 16:1545–1551

    Article  Google Scholar 

  • Shefer D, Rietveld P (1997) Congestion and safety on highways: towards an analytical model. Urban Stud 34(4):679–692

    Article  Google Scholar 

  • Soleimani H, Govindan K, Saghafi H, Jafari H (2017) Fuzzy multi-objective sustainable and green closed-loop supply chain network design. Comput Ind Eng 109:191–203

    Article  Google Scholar 

  • SteadieSeifi M, Dellaert NP, Nuijten W, Van Woensel T, Raoufi R (2014) Multimodal freight transportation planning: a literature review. Eur J Oper Res 233(1):1–15

    Article  MATH  Google Scholar 

  • Suzuki Y (2011) A new truck-routing approach for reducing fuel consumption and pollutants emission. Transp Res D Transport Environ 16(1):73–77

    Article  Google Scholar 

  • Suzuki Y (2016) A dual-objective metaheuristic approach to solve practical pollution routing problem. Int J Prod Econ 176:143–153

    Article  Google Scholar 

  • Szeto WY, Jiang Y, Wang DZW, Sumalee A (2015) A sustainable road network design problem with land use transportation interaction over time. Netw Spat Econ 15(3):791–822

    Article  MathSciNet  MATH  Google Scholar 

  • Taniguchi E, Thompson RG, Yamada T (2014) Recent trends and innovations in modelling city logistics. Procedia Soc Behav Sci 125:4–14

    Article  Google Scholar 

  • Tavasszy LA, Ruijgrok K, Davydenko I (2012) Incorporating logistics in freight transport demand models: state-of-the-art and research opportunities. Transport Rev 32(2):203–219

    Article  Google Scholar 

  • Teypaz N, Schrenk S, Cung VD (2010) A decomposition scheme for large-scale service network design with asset management. Transp Res E Logist Transp Rev 46(1):156–170

    Article  Google Scholar 

  • Thompson RG, Zhang L (2018) Optimising courier routes in central city areas. Transp Res C Emerging Technol 93:1–12

    Article  Google Scholar 

  • Ubeda S, Arcelus FJ, Faulin J (2011) Green logistics at Eroski: a case study. Int J Prod Econ 131(1):44–51

    Article  Google Scholar 

  • Validi S, Bhattacharya A, Byrne PJ (2014) Integrated low- carbon distribution system for the demand side of a product distribution supply chain: a DOE-guided MOPSO optimizer-based solution approach. Int J Prod Res 52(10):3074–3096

    Article  Google Scholar 

  • Verma M, Verter V (2010) A lead-time based approach for planning rail–truck intermodal transportation of dangerous goods. Eur J Oper Res 202(3):696–706

    Article  MATH  Google Scholar 

  • Visser J, Van Binsbergen A, Nemoto T (1999) Urban freight transport policy and planning. In: Taniguchi E, Thompson RG (eds) First International Symposium on City Logistics. Institute of Systems Science Research, Kyoto, Japan, pp 39–69

    Google Scholar 

  • Visser J, Nemoto T, Browne M (2014) Home delivery and the impacts on urban freight transport: a review. Procedia Soc Behav Sci 125:15–27

    Article  Google Scholar 

  • Wadud Z, Aye L, Beer T, Watson H (2006) Modeling Australian road transport emissions till 2025. J Civ Eng 34(2):115–127

    Google Scholar 

  • Wang C, Quddus MA, Ison SG (2009) Impact of traffic congestion on road accidents: a spatial analysis of the M25 motorway in England. Accid Anal Prev 41(4):798–808

    Article  Google Scholar 

  • Wang F, Lai X, Shi N (2011) A multi-objective optimization for green supply chain network design. Decis Support Syst 51(2):262–269

    Article  Google Scholar 

  • Wanke P, Correa P, Jacob J, Santos T (2015) Including carbon emissions in the planning of logistic networks: a Brazilian case. Int J Shipp Transport Logist 7(6):655–675

    Article  Google Scholar 

  • Wong EY, Tai AH, Zhou E (2018) Optimising truckload operations in third-party logistics: a carbon footprint perspective in volatile supply chain. Transp Res D Transport Environ 63:649–661

    Article  Google Scholar 

  • World Business Council for Sustainable Development, World Resources Institute (2001) The greenhouse gas protocol: a corporate accounting and reporting standard. World Resources Institute, Washington, DC

    Google Scholar 

  • World Urbanization Prospects (2018) The 2018 revision. Retrieved from http://esa.un.org/unpd/wup/Publications/Files/WUP2018-KeyFacts.pdf. Accessed 10 Apr 2018

  • Xu M, Lam WH, Gao Z, Grant-Muller S (2016) An activity-based approach for optimisation of land use and transportation network development. Transp B Transport Dyn 4(2):111–134

    Google Scholar 

  • Zhalechian M, Tavakkoli-Moghaddam R, Zahiri B, Mohammadi M (2016) Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty. Transp Res E Logist Transp Rev 89:182–214

    Article  Google Scholar 

  • Zhu W, Erikstad SO, Nowark MP (2014) Emission allocation problems in the maritime logistics chain. EURO J Transp Logist 3(1):35–54

    Article  Google Scholar 

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Funding

This study was supported by the MOSTLOG—A multi-objective approach for a SusTainable LOGistic system—Project funded by the University Federico II of Naples, D.R. 341, 8 February 2016.

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Correspondence to Maria Elena Nenni.

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Communicated by P. Beraldi, M. Boccia, C. Sterle.

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Nenni, M.E., Sforza, A. & Sterle, C. Sustainability-based review of urban freight models. Soft Comput 23, 2899–2909 (2019). https://doi.org/10.1007/s00500-019-03786-x

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