Skip to main content

A bi-level optimization model of LRP in collaborative logistics network considered backhaul no-load cost

  • Focus
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

In collaborative logistics network, all task demands are centralized by logistics platform for resource allocation, and then resource owners execute discretely under final plan. The key point of this study is to effectively balance the different appeals of stakeholders. In this paper, a bi-level programming model is presented to solve multi-deport LRP considered the constraint of hard time window, vehicle capacity and vehicle backhaul cost, which aims at achieving the effective interest coordination between upper layer platform and lower layer vehicle owners. To solve this bi-level model, genetic algorithm is redesigned according to this specific situation. Optimal results of simulation sample show that the satisfied solution for both platform and vehicle owners could be obtained using this method. Feasibility and validity of this model and adaptive algorithm have been verified in the paper. The bi-level model provides a practical and effective method to solve the profit distribution problem between platform and vehicle owners.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Ai TJ, Kachitvichyanukul V (2009) A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery. Comput Oper Res 36(5):1693–1702

    Article  MATH  Google Scholar 

  • Allahyari S, Salari M, Vigo D (2015) A hybrid metaheuristic algorithm for the multi-depot covering. Eur J Oper Res 242(3):756–768

    Article  MATH  Google Scholar 

  • Alves MJ, Costa JP (2014) An algorithm based on particle swarm optimization for multi objective bilevel linear problems. Appl Math Comput 247:547–561

    MathSciNet  MATH  Google Scholar 

  • Ambrosino D, Sciomachen A, Scutellà MG (2009) A heuristic based on multi-exchange techniques for a regional fleet assignment location-routing problem. Comput Oper Res 36(2):442–460

    Article  MATH  Google Scholar 

  • Belhaiza S, Hansen P, Laporte G (2014) A hybrid variable neighborhood tabu search heuristic for the vehicle routing problem with multiple time windows. Comput Oper Res 52:269–281

    Article  MathSciNet  MATH  Google Scholar 

  • Ben-Ayed O, Blair CE (1990) Computational difficulties of bilevel linear programming. Informs, Catonsville

  • Boventer V (1961) The relationship between transportation costs and location rent in transportation problems. J Reg Sci 3(2):27–40

    Article  Google Scholar 

  • Bracken J, Mcgill JT (1973) A convex programming model for optimizing SLBM attack of bomber bases. Oper Res 21(1):30–36

    Article  MathSciNet  MATH  Google Scholar 

  • Buliung RN, Soltys K, Bui R (2010) Catching a ride on the information super-highway: toward an understanding of internet-based carpool formation and use. Transportation 37(6):849–873

    Article  Google Scholar 

  • Chen JF, Wu TH (2006) Vehicle routing problem with simultaneous deliveries and pickup. J Oper Res Soc 57(5):579–587

    Article  MATH  Google Scholar 

  • Defryn C, Sorensen K, Cornelissens T (2016) The selective vehicle routing problem in a collaborative environment. Eur J Oper Res 250(2):400–411

    Article  MathSciNet  MATH  Google Scholar 

  • Dircksen M, Magnin G (2017) Evaluation of synergy potentials in transportation networks managed by a fourth party logistics provider. Transp Res Proc 25:824–841

    Article  Google Scholar 

  • Du J, Li X, Yu L, Dan R, Zhou J (2017) Multi-deport vehicle routing problem for hazardous materials transportation. Inf Sci 399:201–218

    Article  Google Scholar 

  • Errico F, Desaulniers G, Gendreau M, Rei W, Rousseau LM (2016) A priori optimization with recourse for the vehicle routing problem with hard time windows and stochastic service times. Eur J Oper Res 29(1):55–66

    Article  MathSciNet  MATH  Google Scholar 

  • Fattahi M, Govindan K (2016) Integrated forward/reverse logistics network design under uncertainty with pricing for collection of used products. Annu Oper Res 253(1):193–225

    Article  MathSciNet  MATH  Google Scholar 

  • Hossein S, Doulabi H, Seifi A (2013) Lower and upper bounds for location-arc routing problems with vehicle capacity constraints. Eur J Oper Res 24(1):189–208

    MathSciNet  MATH  Google Scholar 

  • Huang M, Cui Y, Yang SX, Wang XW (2013) Fourth party logistics routing problem with fuzzy duration time. Int J Prod Econ 145(1):107–116

    Article  Google Scholar 

  • Ishikawa S, Kubota R, Horio K (2015) Effective hierarchical optimization by a hierarchical multi-space competitive genetic algorithm for the flexible job-shop scheduling problem. Exper Syst Appl 42(24):9434–9440

    Article  Google Scholar 

  • Javid AA, Azad N (2010) Incorporating location, routing and inventory decisions in supply chain network design. Transp Res Part E Log Transp Rev 46(5):582–597

    Article  Google Scholar 

  • Jeroslow RG (1985) The polynomial hierarchy and a simple model for competitive analysis. Math Prog 32(2):146–164

    Article  MathSciNet  MATH  Google Scholar 

  • Jiang DD, Xu ZZ, Wang WQ, Wang YT, Han Y (2015) A collaborative multi-hop routing algorithm for maximum achievable rate. J Netw Comput Appl 57:182–191

    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 

  • Lee H, Zhang T, Boile M (2013) Designing an integrated logistics network in a supply chain system. KSCE J Civ Eng 17(4):806–814

    Article  Google Scholar 

  • Letchford AN, Nasiri SD, Oukil A (2014) Pricing routines for vehicle routing with time windows on road networks. Comput Oper Res 51:331–337

    Article  MathSciNet  MATH  Google Scholar 

  • Li MQ, Lin D, Wang SY (2010) Solving a type of bi-objective bilevel programming problem using NSGA-II. Comput Math Appl 59(2):706–715

    Article  MathSciNet  MATH  Google Scholar 

  • Li X, Zhou JD, Zhao XD (2016) Travel itinerary problem. Transp Res Part B 91:332–343

    Article  Google Scholar 

  • Lu TP, Trappey AJC, Chen YK, Chang YD (2013) Collaborative design and analysis of supply chain network management key processes model. J Netw Comput Appl 36(6):1503–1511

    Article  Google Scholar 

  • McNabb ME, Weir JD, Hill RR, Hall SN (2015) Testing local search move operators on the vehicle routing problem with split deliveries and time windows. Comput Oper Res 56:93–109

    Article  MathSciNet  MATH  Google Scholar 

  • Miranda DM, Conceição SV (2014) The vehicle routing problem with hard time windows and stochastic travel and service time. Exp Syst Appl 64:104–116

    Article  Google Scholar 

  • Nadizadeh A, Nasab H (2014) Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm. Eur J Oper Res 238(2):458–470

    Article  MathSciNet  MATH  Google Scholar 

  • Nagy G, Salhi S (2005) Heuristic algorithms for single and multiple depot vehicle routing problems with pickups and deliveries. Eur J Oper Res 162(1):126–141

    Article  MATH  Google Scholar 

  • Nagy G, Salhi S (2007) Location-routing: issues, models and methods. Eur J Oper Res 177(2):649–672

    Article  MathSciNet  MATH  Google Scholar 

  • Niwa K, Hayashida T, Sakawa M (2010) Computational methods for decentralized two level 0–1 programming problems through distributed genetic algorithms. AIP Conf Proc 1285:1–13

    Google Scholar 

  • Prodhon C, Prins C (2014) A survey of recent research on location-routing problems. Eur J Oper Res 238(1):1–17

    Article  MathSciNet  MATH  Google Scholar 

  • Rieck J, Ehrenberg C, Zimmermann J (2014) Many-to-many location-routing with inter-hub transport and multi-commodity pickup-and-delivery. Eur J Oper Res 236(3):863–878

    Article  MathSciNet  MATH  Google Scholar 

  • Schiffer M, Walther G (2017) The electric location routing problem with time windows and partial recharging. Eur J Oper Res 260:995–1013

    Article  MathSciNet  MATH  Google Scholar 

  • Sinha A, Malo P, Deb K (2017) Evolutionary algorithm for bilevel optimization using approximations of the lower level optimal solution mapping. Eur J Oper Res 257(2):395–411

    Article  MathSciNet  MATH  Google Scholar 

  • Xu XF, Chang WH, Liu J (2017) Resource allocation optimization model of collaborative logistics network based on bilevel programming. Sci Prog 4:1–8

    Google Scholar 

  • Yang F, Wang Y, Yuan W, Jian L (2014) A robust VRPHTW model with travel time uncertainty. J Syst Sci Inf 2(4):289–300

    Google Scholar 

  • Yao JM (2010) Decision optimization analysis on supply chain resource integration in fourth party logistics. J Manuf Syst 29(4):121–129

    Article  Google Scholar 

  • Yu VF, Lin SY (2016) Solving the location-routing problem with simultaneous pickup and delivery by simulated annealing. Int J Product Res 24(2):1–24

    MathSciNet  Google Scholar 

  • Zhang ZB, Zhang SH, Wang YH, Jiang YZ, Wang H (2013) Use of parallel deterministic dynamic programming and hierarchical adaptive genetic algorithm for reservoir operation optimization. Comput Ind Eng 65(2):310–321

    Article  Google Scholar 

  • Zhu J (2014) Non-linear integer programming model and algorithms for connected p-facility location problem. J Syst Sci Inf 2(5):451–460

    Google Scholar 

Download references

Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. 71771208), the Fundamental Research Funds for the Central Universities, China (Grant No. 17CX04023B).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaofeng Xu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

This article does not contain any studies with human participants or animal performed by any of the authors.

Additional information

Communicated by X. Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, X., Zheng, Y. & Yu, L. A bi-level optimization model of LRP in collaborative logistics network considered backhaul no-load cost. Soft Comput 22, 5385–5393 (2018). https://doi.org/10.1007/s00500-018-3056-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-018-3056-6

Keywords