Abstract
City logistics comprise the delivery and picking of goods in urban areas, affecting the performance of businesses and quality of life in cities. The systems that support city logistics for freight transportation have a great research interest for academics, and it is a hot topic for businesses. Research issues like delivery with time windows, traffic congestion, route optimization, and dynamic routing are of great importance in the literature of city logistics. However, that research activity often does not meet practical solutions, and there is a gap between operational research (OR) and business practices in freight transportation. This article presents the development of an information system that supports the efficient delivery of goods within urban areas. The system utilizes a set of OR algorithms enabled by information technologies (IT) to support logistics operations effectively. It mainly deals with optimizing vehicle routes and schedules, while considering the delivery time windows, the specific requirements of customers, the characteristics of the street network, the need for dynamic routing and rerouting, and traffic congestion issues in cities. The article presents the system’s architecture, its development methodology, its basic functionality, the developed algorithms, as well as the adopted information technologies. It concludes with validating the system with real-life business data and the conclusions from the entire effort.
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(adapted from Barker, 2003 p.683)
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References
Adelzadeh M, Asl M, Koosha M (2014) A mathematical model and a solving procedure for multi-depot vehicle routing problem with fuzzy time window and heterogeneous vehicle. Int J Adv Manuf Technol 75(5):793–802. https://doi.org/10.1007/s00170-014-6141-8
Allen J, Browne M, Woodburn A, Leonardi J (2012) The Role of Urban Consolidation Centres in Sustainable Freight Transport. Transp Rev 32(4):473–490. https://doi.org/10.1080/01441647.2012.688074
Angrish A, Starly B, Lee Y-S, Cohen PH (2017) A flexible data schema and system architecture for the virtualization of manufacturing machines (VMM). J Manuf Syst 45:236–247. https://doi.org/10.1016/j.jmsy.2017.10.003
Ballantyne EEF, Lindholm M, Whiteing A (2013) A comparative study of urban freight transport planning: addressing stakeholder needs. J Transp Geogr 32:93–101. https://doi.org/10.1016/j.jtrangeo.2013.08.013
Barceló J, Grzybowska H, Orozco JA (2017) City Logistics. In R. Martí, P. Panos, & M. G. C. Resende (Eds.), Handbook of Heuristics (pp. 1–44). Springer Sci Rev https://doi.org/10.1007/978-3-319-07153-4_55-1
Barker TT (2003) Documentation for Software and IS Development. In H. Bidgoli (Ed.), Encyclopedia of Information Systems (pp. 683–693). Elsevier https://doi.org/10.1016/B0-12-227240-4/00047-2
Björklund M, Martinsen U (2014) From city logistics problems to solutions - a multiple stakeholder perspective. Proceedings of the 26th Conference of the Nordic Logistics Research Network, 346–362
Boudoin D, Morel C, Gardat M (2014) Supply Chains and Urban Logistics Platforms. In: Gonzalez-Feliu J, Semet F, Routhier J-L (eds) Sustainable Urban Logistics: Concepts, Methods and Information Systems. Springer, Berlin Heidelberg, pp 1–20. https://doi.org/10.1007/978-3-642-31788-0_1
Buhmann A, Likely F, Geddes D (2018) Communication evaluation and measurement: connecting research to practice. J Commun Manag 22(1):113–119. https://doi.org/10.1108/JCOM-12-2017-0141
Cherrett T, Allen J, McLeod F, Maynard S, Hickford A, Browne M (2012) Understanding urban freight activity – key issues for freight planning. J Transp Geogr 24:22–32. https://doi.org/10.1016/j.jtrangeo.2012.05.008
Chiang TC, Hsu WH (2014) A knowledge-based evolutionary algorithm for the multiobjective vehicle routing problem with time windows. Comput Oper Res 45:25–37. https://doi.org/10.1016/j.cor.2013.11.014
Crainic TG, Gendreau M, Potvin J-Y (2009) Intelligent freight-transportation systems: Assessment and the contribution of operations research. Transp Res Part C Emerg Technol 17(6):541–557. https://doi.org/10.1016/j.trc.2008.07.002
Dantzig GB, Ramser JH (1959) The Truck Dispatching Problem. Manage Sci 6(1):80–91. https://doi.org/10.1287/mnsc.6.1.80
Elshaer R, Awad H (2020) A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants. Comput Ind Eng 140:106242. https://doi.org/10.1016/j.cie.2019.106242
Erdoğan G (2017) An open source Spreadsheet Solver for Vehicle Routing Problems. Comput Oper Res 84:62–72. https://doi.org/10.1016/j.cor.2017.02.022
Faramarzi A, Heidarinejad M, Stephens B, Mirjalili S (2020) Equilibrium optimizer: A novel optimization algorithm. Knowl Based Syst 191:105190. https://doi.org/10.1016/j.knosys.2019.105190
Gao Y, Wang JW (2021) A resilience assessment framework for urban transportation systems. Int J Prod Res 59(7):2177–2192. https://doi.org/10.1080/00207543.2020.1847339
Gayialis SP, Konstantakopoulos GD, Papadopoulos GA, Kechagias E, Ponis ST (2018) Developing an advanced cloud-based vehicle routing and scheduling system for urban freight transportation. In IFIP Advances in Information and Communication Technology (Vol. 536). Springer International Publishing. https://doi.org/10.1007/978-3-319-99707-0_24
Gayialis SP, Konstantakopoulos GD, Tatsiopoulos IP (2019) Vehicle Routing Problem for Urban Freight Transportation: A Review of the Recent Literature. In: Sifaleras A, Petridis K (eds) Operational Research in the Digital Era--ICT Challenges. Springer P, pp 89–104. https://doi.org/10.1007/978-3-319-95666-4_7Springer
Golini R, Guerlain C, Lagorio A, Pinto R (2018) An assessment framework to support collective decision making on urban freight transport. Transport 33(4):890–901. https://doi.org/10.3846/transport.2018.6591
Groß P-O, Ehmke JF, Mattfeld DC (2019) Cost-Efficient and Reliable City Logistics Vehicle Routing with Satellite Locations under Travel Time Uncertainty. Transp Res Proc 37:83–90. https://doi.org/10.1016/j.trpro.2018.12.169
Homburg C, Kuester S, Beutin N, Menon A (2005) Determinants of Customer Benefits in Business-to-Business Markets: A Cross-Cultural Comparison. J Int Mark 13(3):1–31. https://doi.org/10.1509/jimk.13.3.1
Hong L (2012) An improved LNS algorithm for real-time vehicle routing problem with time windows. Comput Oper Res 39(2):151–163. https://doi.org/10.1016/j.cor.2011.03.006
Hornstra RP, Silva A, Roodbergen KJ, Coelho LC (2020) The vehicle routing problem with simultaneous pickup and delivery and handling costs. Comput Oper Res 115:104858. https://doi.org/10.1016/j.cor.2019.104858
Hu P, Ning H, Chen L, Daneshmand M (2019) An Open Internet of Things System Architecture Based on Software-Defined Device. IEEE Internet Things J 6(2):2583–2592. https://doi.org/10.1109/JIOT.2018.2872028
Jiang J, Ng KM, Poh KL, Teo KM (2014) Vehicle routing problem with a heterogeneous fleet and time windows. Expert Syst Appl 41(8):3748–3760. https://doi.org/10.1016/j.eswa.2013.11.029
Karakikes I, Nathanail E (2021) Validating the Simulated Impacts of Urban Freight Transport. In: Nathanail EG, Adamos G, Karakikes I (eds) Advances in Mobility-as-a-Service Systems. Springer International Publishing, pp 824–834
Kechagias EP, Gayialis SP, Konstantakopoulos GD, Papadopoulos GA (2020a) An Application of a Multi-Criteria Approach for the Development of a Process Reference Model for Supply Chain Operations. Sustainability 12(14):5791. https://doi.org/10.3390/su12145791
Kechagias EP, Gayialis SP, Konstantakopoulos GD, Papadopoulos GA (2020b) An Application of an Urban Freight Transportation System for Reduced Environmental Emissions. Systems 8(4):49. https://doi.org/10.3390/systems8040049
Konstantakopoulos GD, Gayialis SP, Kechagias EP (2020) Vehicle routing problem and related algorithms for logistics distribution: a literature review and classification. Oper Res Int Journal 1(1):1–30 https://doi.org/10.1007/s12351-020-00600-7
Kumar SV (2017) Traffic Flow Prediction using Kalman Filtering Technique. Procedia Eng 187:582–587. https://doi.org/10.1016/j.proeng.2017.04.417
Lagorio A, Gonzalez-Feliu J, Pinto R (2018) Urban freight demand estimation: A probability distribution based method. Inf Syst Logist Supply Chain Proc, 415–422
Li Q, Miao L (2003) Integration of China’s intermodal freight transportation and ITS technologies. Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems, 1, 715–719 vol.1. https://doi.org/10.1109/ITSC.2003.1252044
Lin C, Choy KL, Ho GTS, Chung SH, Lam HY (2014) Survey of Green Vehicle Routing Problem: Past and future trends. Expert Syst Appl 41:1118–1138
Nwaogbe OR, Omoke V, Ubani EC, Ukaegbu SI (2013) Cost minimisation of product transhipment for physical distribution management: original research. J Transp Supply Chain Manag 7(1):1–9. https://doi.org/10.4102/jtscm.v7i1.94
OMG (2017) OMG Unified modeling language Version: 2.5.1. https://www.omg.org/spec/UML/2.5.1/PDF
Perboli G, Rosano M (2018) A Decision Support System for Optimizing the Last-Mile by Mixing Traditional and Green Logistics. In: Temponi C, Vandaele N (eds) Information Systems, Logistics, and Supply Chain. Springer International Publishing, pp 28–46
Qiao W, Yang Z (2019) Solving Large-Scale Function Optimization Problem by Using a New Metaheuristic Algorithm Based on Quantum Dolphin Swarm Algorithm. IEEE Access 7:138972–138989. https://doi.org/10.1109/ACCESS.2019.2942169
Rantala J (2009) Effects of e-Business on Logistics and Urban Freight Transportations. WEBIST
Russo F, Rindone C, Agostino PD, Lanciano C, Scattarreggia T (2015) A city logistics system for long distance freight transport provisioning. WIT Transactions on The Built Environment 146:279–290. https://doi.org/10.2495/UT150221
Samareh Moosavi SH, Bardsiri VK (2019) Poor and rich optimization algorithm: A new human-based and multi populations algorithm. Eng Appl Artif Intell 86:165–181. https://doi.org/10.1016/j.engappai.2019.08.025
Schau V, Apel S, Gebhardt K, Kretzschmar J, Stolcis C, Mauch M, Buchholz J (2016) Intelligent Infrastructure for Last-mile and Short-distance Freight Transportation with Electric Vehicles in the Domain of Smart City Logistic. Vehits, 149–159
Sheer AW (2000) ARIS - Business Process Modeling. Springer-Verlag, Berlin Heidelberg. https://doi.org/10.1007/978-3-642-57108-4
Software AG (2018) ARIS Architect & Designer. https://www.softwareag.com/nl/products/aris_alfabet/bpa/aris_architect/default
Software AG (2021) Epc in Aris Cheat Sheet. https://www.ariscommunity.com/system/files/EPC_cheat_sheet.pdf
Solomon MM (1987) Algorithms for the vehicle routing and scheduling problems with time window constraints. Oper Res 35(2):254–265. https://doi.org/10.1287/opre.35.2.254
Sopha BM, Siagian A, Sri Asih AM (2016) Simulating Dynamic Vehicle Routing Problem using Agent-Based Modeling and Simulation. 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 1335–1339. https://doi.org/10.1109/IEEM.2016.7798095
Taniguchi E, Thompson RG, Yamada T (2004) Visions for City Logistics. In E. Taniguchi & R. G. Thompson (Eds.), Logistics Systems for Sustainable Cities (pp. 1–16). Emerald Group Publishing Limited. https://doi.org/10.1108/9780080473222-001
Taniguchi E, Thompson RG, Yamada T (2014) Recent Trends and Innovations in Modelling City Logistics. Procedia Soc and behav Sciences 125:4–14. https://doi.org/10.1016/j.sbspro.2014.01.1451
Van Duin J, Bauwens J, Enserink B, Tavasszy L, Wong K (2016) Risk-aware roadmapping for city logistics in 2025
Wu W, Tsai WT, Li W (2013) Creative software crowdsourcing: from components and algorithm development to project concept formations. Int J Creat Comput 1(1):57. https://doi.org/10.1504/IJCRC.2013.056925
Zhang A, Zhong RY, Farooque M, Kang K, Venkatesh VG (2020) Blockchain-based life cycle assessment: An implementation framework and system architecture. Resour Conserv Recycl 152:104512. https://doi.org/10.1016/j.resconrec.2019.104512
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Gayialis, S.P., Kechagias, E.P. & Konstantakopoulos, G.D. A city logistics system for freight transportation: integrating information technology and operational research. Oper Res Int J 22, 5953–5982 (2022). https://doi.org/10.1007/s12351-022-00695-0
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DOI: https://doi.org/10.1007/s12351-022-00695-0