Skip to main content

Advertisement

SpringerLink
Log in

An improved optimization algorithm for a multi-depot vehicle routing problem considering carbon emissions

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

In a multi-depot vehicle routing problem (MDVRP) of same-city delivery, driving distance and actual loading can greatly influence the amount of carbon emissions generated. This paper considers fuel and carbon emission costs as part of total costs, proposes a MDVRP with minimized logistics costs and driven distance, and then establishes a mixed integer programming model. An improved chemical reaction optimization algorithm is also designed by considering this problem’s characteristics (i.e., a greedy search strategy is presented to generate an initial population), and two coding approaches (i.e., two-part coding and matrix coding) are applied prior to designing four chemical reaction operators. The simulation experiment is carried out using a set of a random instances and the experimental results demonstrate that one can reduce carbon emissions by driving extra lesser distances, providing a methodological guide for MDVRPs with logistics costs and carbon emissions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

Data availability

Not applicable.

References

  • Azadeh A, Farrokhi-Asl H (2019) The close–open mixed multi depot vehicle routing problem considering internal and external fleet of vehicles[J]. Transp Lett 11(2):78–92

    Article  Google Scholar 

  • Bae H (2016) Moon I (2016) Multi-depot vehicle routing problem with time windows considering delivery and installation vehicles. Appl Math Model 40(13):6536–6549

    Article  Google Scholar 

  • Bechikh S, Chaabani A, Ben SL (2014) An efficient chemical reaction optimization algorithm for multiobjective optimization. IEEE Trans Cybern 45(10):2051–2064

    Article  Google Scholar 

  • Birol Y, Gokcil E, Guvenc MA, Akdi S (2016) Processing of high strength EN AW 6082 forgings without a solution heat treatment. Mat Sci Eng A-Struct 674:25–32

    Article  CAS  Google Scholar 

  • Brandão J (2020) A memory-based iterated local search algorithm for the multi-depot open vehicle routing problem. Eur J Oper Res 2:34–56

    Google Scholar 

  • Breunig U, Baldacci R, Hartl RF, Vidal T (2019) The electric two-echelon vehicle routing problem. Comput Oper Res 103:198–210

    Article  Google Scholar 

  • Choi D, Gao Z, Jiang W (2020) Attention to global warming. Rev Financ Stud 33(3):1112–1145

    Article  Google Scholar 

  • Chu J C Y, Chen A Y, Shih H H (2020) Stochastic programming model for integrating bus network design and dial-a-ride scheduling[J]. Transp Lett 1–13

  • Dam TL, Li K, Fournier-Viger P (2017) Chemical Reaction Optimization with Unified Tabu Search for the Vehicle Routing Problem. Soft Comput 21(21):6421–6433

    Article  Google Scholar 

  • Dantzig GB, Ramser JH (1959) The Truck Dispatching Problem. Manage Sci 6(1):80–91

    Article  Google Scholar 

  • de Oliveira FB, Enayatifar R, Sadaei HJ, Guimarães FG, Potvin JY (2016) A cooperative coevolutionary algorithm for the multi-depot vehicle routing problem. Expert Syst Appl 43:117–130

    Article  Google Scholar 

  • Erdoğan S, Miller-Hooks E (2012) A green vehicle routing problem. Transp Res Part E Logist Transp Rev 48(1):100–114

    Article  Google Scholar 

  • Feo TA, Resende MGC (1995) Greedy randomized adaptive search procedures. J Glob Optim 6(2):109–133

    Article  Google Scholar 

  • Hadidi A (2017) Optimization of electrically separated two-stage thermoelectric refrigeration systems using chemical reaction optimization algorithm. Appl Therm Eng 123:514–526

    Article  CAS  Google Scholar 

  • Holland JH (1992) Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. MIT press

  • 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

  • Karagul K, Sahin Y, Aydemir E, Oral A(2019) A simulated annealing algorithm based solution method for a green vehicle routing problem with fuel consumption, In: Lean and Green Supply Chain Management. Springer, pp 161–187

  • Jabir E, Panicker V, Sridharan R (2017) Design and development of a hybrid ant colony-variable neighbourhood search algorithm for a multi-depot green vehicle routing problem. Transp Res Part D Transp Environ 57:422–457

    Article  Google Scholar 

  • Karakatič S, Podgorelec V (2015) A survey of genetic algorithms for solving multi depot vehicle routing problem. Appl Soft Comput 27:519–532

    Article  Google Scholar 

  • Koç Ç, Karaoglan I (2016) The green vehicle routing problem: A heuristic based exact solution approach. Appl Soft Comput 39:154–164

    Article  Google Scholar 

  • Lam AYS, Li VOK (2009) Chemical-reaction-inspired metaheuristic for optimization. IEEE Trans Evol Comput 14(3):381–399

    Article  Google Scholar 

  • Laporte P (1984) Status of language planning in Quebec: An evaluation. Conflict and language planning in Quebec, pp 53–80

  • Lam AYS, Li VOK (2012) Chemical reaction optimization: A tutorial. Memetic Comput 4(1):3–17

    Article  Google Scholar 

  • Li, Hongye et al (2018) A Decomposition-Based Chemical Reaction Optimization for Multi-Objective Vehicle Routing Problem for Simultaneous Delivery and Pickup with Time Windows. Memetic Computing

  • Li J, Wang D, Zhang J (2018) Heterogeneous fixed fleet vehicle routing problem based on fuel and carbon emissions. J Clean Prod 201:896–908

    Article  Google Scholar 

  • Li J, Li Y, Pardalos PM (2016) Multi-depot vehicle routing problem with time windows under shared depot resources. J Comb Optim 31:515–532

    Article  Google Scholar 

  • Lin J, Fu P, Li X, Zhang J, Zhu D (2015) Study on Vehicle Routing Problem and Tabu Search Algorithmunder Low-carbon Environment. Chin J Manag Sci 23:98–106

    Google Scholar 

  • Lin T, Rodríguez LF, Davis S, Khanna M, Shastri Y, Grift T, Ting KC (2016) Biomass feedstock preprocessing and long-distance transportation logistics. Gcb Bioenergy 8(1):160–170

    Article  CAS  Google Scholar 

  • Nadizadeh A, Kafash B (2019) Fuzzy capacitated location-routing problem with simultaneous pickup and delivery demands[J]. Transp Lett 11(1):1–19

    Article  Google Scholar 

  • Niu Y, Yang Z, Chen P, Xiao J (2018) Optimizing the green open vehicle routing problem with time windows by minimizing comprehensive routing cost. J Clean Prod 171:962–971

    Article  Google Scholar 

  • Nikfarjam A, Moosavi A (2021) An integrated (1, T) inventory policy and vehicle routing problem under uncertainty: an accelerated Benders decomposition algorithm[J]. Transp Lett 13(2):104–124

    Article  Google Scholar 

  • Padmanabhan B, Huynh N, Ferrell W, et al (2021) Potential benefits of carrier collaboration in vehicle routing problem with pickup and delivery[J]. Transp Lett 1–16

  • Poonthalir G, Nadarajan R (2018) A Fuel Efficient Green Vehicle Routing Problem with varying speed constraint (F-GVRP). Expert Syst Appl 100:131–144

    Article  Google Scholar 

  • Qin, Gaoyuan, Fengming Tao, and Lixia Li (2019a) A Vehicle Routing Optimization Problem for Cold Chain Logistics Considering Customer Satisfaction and Carbon Emissions. Int. J. Environ. Res. Public Health 16(4):576

  • Qin G, Tao F, Li L, Chen Z (2019b) Optimization of the Simultaneous Pickup and Delivery Vehicle Routing Problem Based on Carbon Tax. Ind Manage Data Syst 119(9):2055–2071

    Article  Google Scholar 

  • Ramos TRP, Gomes MI, Barbosa-Póvoa AP(2019) A new matheuristic approach for the multi-depot vehicle routing problem with inter-depot routes. OR Spectr 1–36

  • Sacramento D, Pisinger D, Ropke S (2019) An adaptive large neighborhood search metaheuristic for the vehicle routing problem with drones. Transport Res C-Emer 102:289–315

    Article  Google Scholar 

  • Salhi S, Imran A, Wassan NA (2014) The multi-depot vehicle routing problem with heterogeneous vehicle fleet: Formulation and a variable neighborhood search implementation. Comput Oper Res 52:315–325

    Article  Google Scholar 

  • Sarasola B, Doerner KF (2020) Adaptive large neighborhood search for the vehicle routing problem with synchronization constraints at the delivery location. Networks 75(1):64–85

    Article  Google Scholar 

  • Shen L, Tao F, Wang S (2018) Multi-Depot Open Vehicle Routing Problem with Time Windows Based on Carbon Trading. Int J Environ Res Public Health 15(9):2025

    Article  Google Scholar 

  • Shi Y, Lv L, Hu F, Han Q (2020) A heuristic solution method for multi-depot vehicle routing-based waste collection problems. Appl Sci 10(7):2403

    Article  CAS  Google Scholar 

  • Singh V, Ganapathy L, Pundir AK (2019) An Improved Genetic Algorithm for Solving Multi Depot Vehicle Routing Problems. Int J Inf Syst Supply Chain Manag 12(4):1–26

    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, Liu Y, Ho SC (2016) Chemical reaction optimization for solving a static bike repositioning problem. Transp Res Part D Transp Environ 47:104–135

    Article  Google Scholar 

  • Truong TK, Li K, Xu Y (2013) Chemical reaction optimization with greedy strategy for the 0–1 knapsack problem. Appl Soft Comput 13(4):1774–1780

    Article  Google Scholar 

  • Vincent FY, Redi AANP, Hidayat YA, Wibowo OJ (2017) A simulated annealing heuristic for the hybrid vehicle routing problem. Appl Soft Comput 53:119–132

    Article  Google Scholar 

  • Wang S, Tao F, Shi Y (2018) Optimization of Inventory Routing Problem in Refined Oil Logistics with the Perspective of Carbon Tax[J]. Energies 11:1437

    Article  Google Scholar 

  • Xiao Y, Konak A (2016) The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion. Transport Res E-log 88:146–166

    Article  Google Scholar 

  • Yao B, Cao Q, Wang Z et al (2016) A two-stage heuristic algorithm for the school bus routing problem with mixed load plan[J]. Transp Lett 8(4):205–219

    Article  Google Scholar 

  • Žunić E, Delalić S, Đonko D (2020) Adaptive multi-phase approach for solving the realistic vehicle routing problems in logistics with innovative comparison method for evaluation based on real GPS data[J]. Transp Lett 1–14

Download references

Funding

National Natural Science Foundation of China (71871105).

Author information

Authors and Affiliations

  1. School of Business, Jiangnan University, Wuxi, 214122, China

    Xujin Pu & Xulong Lu

  2. School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, 200030, China

    Guanghua Han

Authors
  1. Xujin Pu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xulong Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guanghua Han
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Xujin Pu and Guanghua Han conceived this study, Xulong Lu and Xujin Pu conducted and drafted the context. Xujin Pu and Guanghua Han designed the algorithm. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Guanghua Han.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Responsible Editor: Philippe Garrigues

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pu, X., Lu, X. & Han, G. An improved optimization algorithm for a multi-depot vehicle routing problem considering carbon emissions. Environ Sci Pollut Res 29, 54940–54955 (2022). https://doi.org/10.1007/s11356-022-19370-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-022-19370-0

Keywords

Search

Navigation