Abstract
We introduce the bi-objective emissions disturbance traveling salesman problem (BEDTSP), which aims at minimizing carbon dioxide emissions (\(\hbox {CO}_2\)) as well as disturbance to urban neighborhoods, when planning the tour of a single vehicle delivering goods to customers. Although there exist recent studies on minimizing emissions, we are not aware of any work on minimizing disturbance. We develop four different mathematical models for the BEDTSP. We also develop several data generation strategies for minimizing disturbance. These strategies consider optional nodes, thus allowing detours that yield less disturbance but also possibly more emissions. All models and strategies are compared in an extensive computational study. Experimental results allow us to derive clear guidelines for which model and data generation strategy to use in which context. Following these guidelines, we conduct a case study for the city of Vienna.
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References
Applegate DL, Bixby RE, Chvatal V, Cook WJ (2011) The traveling salesman problem: a computational study. Princeton University Press, Princeton
Barth M, Boriboonsomsin K (2009) Energy and emissions impacts of a freeway-based dynamic eco-driving system. Transp Res Part D Transp Environ 14(6):400–410
Bektaş T, Laporte G (2011) The pollution-routing problem. Transp Res Part B Methodol 45(8):1232–1250
Boland N, Charkhgard H, Savelsbergh M (2015) A criterion space search algorithm for biobjective integer programming—the balanced box method. INFORMS J Comput 27(4):735–754
Chankong V, Haimes YY (1983) Multiobjective decision making: theory and methodology. Elsevier Science, New York
Demir E, Bektaş T, Laporte G (2014) The bi-objective pollution-routing problem. Eur J Oper Res 232(3):464–478
Demir E, Huang Y, Scholts S, Van Woensel T (2015) A selected review on the negative externalities of the freight transportation: modeling and pricing. Transp Res Part E Log Transp Rev 77:95–114
Dolan ED, Moré JJ (2002) Benchmarking optimization software with performance profiles. Math Progr 91(2):201–213
Doppstadt C, Koberstein A, Vigo D (2016) The hybrid electric vehicle-traveling salesman problem. Eur J Oper Res 253(3):825–842
Ehrgott M, Gandibleux X (2000) A survey and annotated bibliography of multiobjective combinatorial optimization. OR Spektrum 22(4):425–460
European Commission (2011) White paper Roadmap to a single european transport area: towards a competitive and resource efficient transport system
Franceschetti A, Honhon D, Van Woensel T, Bektaş T, Laporte G (2013) The time-dependent pollution-routing problem. Transp Res Part B Methodol 56:265–293
Gandibleux X, Beugnies F, Randriamasy S (2006) Martins’ algorithm revisited for multi-objective shortest path problems with a maxmin cost function. 4OR 4(1):47–59
Garaix T, Artigues C, Feillet D, Josselin D (2010) Vehicle routing problems with alternative paths: an application to on-demand transportation. Eur J Oper Res 204(1):62–75
Gendreau M, Laporte G, Semet F (1998) A tabu search heuristic for the undirected selective travelling salesman problem. Eur J Oper Res 106(2):539–545
Golden BL, Levy L, Vohra R (1987) The orienteering problem. Naval Res Logist 34(3):307–318
Gutin G, Punnen AP (2006) The traveling salesman problem and its variations, vol 12. Springer, Berlin
Hamacher HW, Pedersen CR, Ruzika S (2007) Finding representative systems for discrete bicriterion optimization problems. Oper Res Lett 35(3):336–344
Hansen MP, Jaszkiewicz A (1998) Evaluating the quality of approximations to the non-dominated set. IMM, Department of Mathematical Modelling, Technical Universityof Denmark
Hansen P (1980) Bicriterion path problems. In: Fandel G, Gal T (eds) Multiple criteria decision making theory and application. Lecture notes in economics and mathematical systems, vol 177. Springer, Berlin, Heidelberg, pp 109–127
Hiermann G, Puchinger J, Ropke S, Hartl RF (2016) The electric fleet size and mix vehicle routing problem with time windows and recharging stations. Eur J Oper Res 252(3):995–1018
Kara I, Kara BY, Yetis MK (2007) Energy minimizing vehicle routing problem. In: Dress A, Xu Y, Zhu B (eds) Proceedings of the combinatorial optimization and applications: first international conference, COCOA 2007, Xi’an, China, August 14–16, 2007. Springer, Berlin, pp 62–71
London Department of Transport (2014) Quiet deliveries good practice guidance: key principles and processes for retailers. https://www.gov.uk/government/publications/quiet-deliveries-demonstration-scheme. Accessed 20 Mar 2017
Magistrat der Stadt Wien (2014) Smart City Wien—Rahmenstrategie. https://smartcity.wien.gv.at/site/wp-content/blogs.dir/3/files/2014/08/Langversion_SmartCityWienRahmenstrategie_deutsch_doppelseitig.pdf. Accessed 20 Mar 2017
Martins EQV (1984) On a multicriteria shortest path problem. Eur J Oper Res 16(2):236–245
Miller C, Zemlin R, Tucker A (1960) Integer programming formulation of traveling salesman problems. J ACM (JACM) 7(4):326–329
Palmer A (2007) The development of an integrated routing and carbon dioxide emissions model for goods vehicles. Ph.D. thesis, Cranfield University, School of Management
Roberti R, Wen M (2016) The electric traveling salesman problem with time windows. Transp Res Part E Logist Transp Rev 89:32–52
Serafini P (1987) Some considerations about computational complexity for multi objective combinatorial problems. In: Jahn J, Krabs W (eds) Recent advances and historical development of vector optimization. Lecture notes in economics and mathematical systems, vol 294. Springer, Berlin, Heidelberg, pp 222–232
Suzuki Y (2011) A new truck-routing approach for reducing fuel consumption and pollutants emission. Transp Res Part D Transp Environ 16(1):73–77
Suzuki Y (2016) A dual-objective metaheuristic approach to solve practical pollution routing problem. Int J Prod Econ 176:143–153
Tadei R, Perboli G, Perfetti F (2017) The multi-path traveling salesman problem with stochastic travel costs. EURO J Transp Logist 6:1–21
Tricoire F (2012) Proute. GitHub https://github.com/fa-bien/proute
Tricoire F, Romauch M, Doerner KF, Hartl RF (2010) Heuristics for the multi-period orienteering problem with multiple time windows. Comput Oper Res 37(2):351–367
Tricoire F, Parragh SN (2017) Investing in logistics facilities today to reduce routing emissions tomorrow. Transp Res Part B Methodol 103:56–67
United Nations Department of Economic and Social Affairs (2014) World urbanization prospects: the 2014 revision. ST/ESA/SERA/352
United Parcel Service of America Inc (2016) Pulse of the online shopper-A UPS white paper
VIENNAat (2012) City-Maut für Wien wieder im Gespräch. http://www.vienna.at/city-maut-fuer-wien-wieder-im-gespraech/3258278. Accessed 20 Mar 2017
Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Trans Evolut Comput 3(4):257–271
Zitzler E, Thiele L, Laumanns M, Fonseca CM, Da Fonseca VG (2003) Performance assessment of multiobjective optimizers: an analysis and review. IEEE Trans Evolut Comput 7(2):117–132
Acknowledgements
The present research has been conducted in the context of the Green City Hubs Project, #FA379051 funded by Austrian Research Promotion Agency (FFG). We want to thank Christoph Six from the Institute for Powertrains and Automotive Technology of the Technical University of Vienna and Andreas Krawinkler from our department for providing us with real-world data.
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Grabenschweiger, J., Tricoire, F. & Doerner, K.F. Finding the trade-off between emissions and disturbance in an urban context. Flex Serv Manuf J 30, 554–591 (2018). https://doi.org/10.1007/s10696-017-9297-3
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DOI: https://doi.org/10.1007/s10696-017-9297-3