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Hybrid artificial immune algorithm for optimizing a Van-Robot E-grocery delivery system

Author

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  • Liu, Dan
  • Yan, Pengyu
  • Pu, Ziyuan
  • Wang, Yinhai
  • Kaisar, Evangelos I.

Abstract

Same-day delivery and on-demand delivery with driverless delivery robots (DDRs) are becoming new attractive options for more customers looking for grocery or medication delivery, as these delivery methods can customize time demand and meet consumers’ safety expectations. However, meeting these requirements for instant shipping necessarily increases the need for more vans and DDRs for last-mile delivery, thus increasing the economic and ecological costs. To optimize the economic costs and environmental effects of the delivery network, and also to meet customer satisfaction simultaneously, an effective model considering the new constraints of the van-DDR system and an efficient algorithm are needed to obtain the solutions. Therefore, the goals of this study are to establish a model and develop an algorithm for a multi-objective multi-depot two-tier location routing problem with parcel transshipment (MOMD-2T-LRP-PT), where vans and DDRs serve the two tiers, respectively. In this study, we split the MOMD-2T-LRP-PT model into two subproblems: the location-allocation problem and the vehicle routing problem. The two problems are solved sequentially and iteratively with a “k-prototype cluster” and a hybrid artificial immune algorithm (HAIA). We firstly illustrate the effectiveness of the MOMD-2T-LRP-PT model with the ∊-constraint method on a small-scale data set. Then the proposed HAIA algorithm is compared with a nondominated sorting genetic algorithm II (NSGA-II) using different data sets including a real case test. Both the analytic results and the real case application show that the ∊-constraint method can produce the best solution with up to six customers, and the HAIA algorithm produces better-optimized results than NSGA-II in real-life applications. These results imply that the MOMD-2T-LRP-PT model and the proposed HAIA algorithm are promising and effective in optimizing practical E-grocery delivery that can achieve optimization and balance among economic costs, environmental effects, and customer satisfaction.

Suggested Citation

  • Liu, Dan & Yan, Pengyu & Pu, Ziyuan & Wang, Yinhai & Kaisar, Evangelos I., 2021. "Hybrid artificial immune algorithm for optimizing a Van-Robot E-grocery delivery system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    • Handle: RePEc:eee:transe:v:154:y:2021:i:c:s1366554521002295
    DOI: 10.1016/j.tre.2021.102466
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    as
    1. Grangier, Philippe & Gendreau, Michel & Lehuédé, Fabien & Rousseau, Louis-Martin, 2016. "An adaptive large neighborhood search for the two-echelon multiple-trip vehicle routing problem with satellite synchronization," European Journal of Operational Research, Elsevier, vol. 254(1), pages 80-91.
    2. Li, Hongqi & Liu, Yinying & Jian, Xiaorong & Lu, Yingrong, 2018. "The two-echelon distribution system considering the real-time transshipment capacity varying," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 239-260.
    3. Teodor Gabriel Crainic & Nicoletta Ricciardi & Giovanni Storchi, 2009. "Models for Evaluating and Planning City Logistics Systems," Transportation Science, INFORMS, vol. 43(4), pages 432-454, November.
    4. Barreto, Sergio & Ferreira, Carlos & Paixao, Jose & Santos, Beatriz Sousa, 2007. "Using clustering analysis in a capacitated location-routing problem," European Journal of Operational Research, Elsevier, vol. 179(3), pages 968-977, June.
    5. Goeke, D. & Schneider, M., 2015. "Routing a Mixed Fleet of Electric and Conventional Vehicles," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65939, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 126189, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Erdoğan, Sevgi & Miller-Hooks, Elise, 2012. "A Green Vehicle Routing Problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 100-114.
    8. Kitjacharoenchai, Patchara & Min, Byung-Cheol & Lee, Seokcheon, 2020. "Two echelon vehicle routing problem with drones in last mile delivery," International Journal of Production Economics, Elsevier, vol. 225(C).
    9. Attila A. Kovacs & Bruce L. Golden & Richard F. Hartl & Sophie N. Parragh, 2015. "The Generalized Consistent Vehicle Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 796-816, November.
    10. Nico Dellaert & Fardin Dashty Saridarq & Tom Van Woensel & Teodor Gabriel Crainic, 2019. "Branch-and-Price–Based Algorithms for the Two-Echelon Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 53(2), pages 463-479, March.
    11. Gerard Cornuejols & Marshall L. Fisher & George L. Nemhauser, 1977. "Exceptional Paper--Location of Bank Accounts to Optimize Float: An Analytic Study of Exact and Approximate Algorithms," Management Science, INFORMS, vol. 23(8), pages 789-810, April.
    12. Simoni, Michele D. & Kutanoglu, Erhan & Claudel, Christian G., 2020. "Optimization and analysis of a robot-assisted last mile delivery system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    13. CORNUEJOLS, Gérard & FISHER, Marshall L. & NEMHAUSER, George L., 1977. "Location of bank accounts to optimize float: An analytic study of exact and approximate algorithms," LIDAM Reprints CORE 292, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Li, Hongqi & Wang, Haotian & Chen, Jun & Bai, Ming, 2020. "Two-echelon vehicle routing problem with time windows and mobile satellites," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 179-201.
    15. Guido Perboli & Roberto Tadei & Daniele Vigo, 2011. "The Two-Echelon Capacitated Vehicle Routing Problem: Models and Math-Based Heuristics," Transportation Science, INFORMS, vol. 45(3), pages 364-380, August.
    16. Lin, C.K.Y. & Kwok, R.C.W., 2006. "Multi-objective metaheuristics for a location-routing problem with multiple use of vehicles on real data and simulated data," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1833-1849, December.
    17. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1085-1099.
    18. Michael Drexl, 2012. "Synchronization in Vehicle Routing---A Survey of VRPs with Multiple Synchronization Constraints," Transportation Science, INFORMS, vol. 46(3), pages 297-316, August.
    19. Figliozzi, Miguel & Saenz, Jesus & Faulin, Javier, 2020. "Minimization of urban freight distribution lifecycle CO2e emissions: Results from an optimization model and a real-world case study," Transport Policy, Elsevier, vol. 86(C), pages 60-68.
    20. Martínez-Salazar, Iris Abril & Molina, Julian & Ángel-Bello, Francisco & Gómez, Trinidad & Caballero, Rafael, 2014. "Solving a bi-objective Transportation Location Routing Problem by metaheuristic algorithms," European Journal of Operational Research, Elsevier, vol. 234(1), pages 25-36.
    21. Govindan, K. & Jafarian, A. & Khodaverdi, R. & Devika, K., 2014. "Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food," International Journal of Production Economics, Elsevier, vol. 152(C), pages 9-28.
    22. Roberto Baldacci & Aristide Mingozzi & Roberto Roberti & Roberto Wolfler Calvo, 2013. "An Exact Algorithm for the Two-Echelon Capacitated Vehicle Routing Problem," Operations Research, INFORMS, vol. 61(2), pages 298-314, April.
    23. M Wen & J Larsen & J Clausen & J-F Cordeau & G Laporte, 2009. "Vehicle routing with cross-docking," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1708-1718, December.
    24. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    25. Goeke, Dominik & Schneider, Michael, 2015. "Routing a mixed fleet of electric and conventional vehicles," European Journal of Operational Research, Elsevier, vol. 245(1), pages 81-99.
    26. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    27. Zhen, Lu & Ma, Chengle & Wang, Kai & Xiao, Liyang & Zhang, Wei, 2020. "Multi-depot multi-trip vehicle routing problem with time windows and release dates," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    28. Li, Hongqi & Wang, Haotian & Chen, Jun & Bai, Ming, 2021. "Two-echelon vehicle routing problem with satellite bi-synchronization," European Journal of Operational Research, Elsevier, vol. 288(3), pages 775-793.
    29. Michael Schneider & Maximilian Löffler, 2019. "Large Composite Neighborhoods for the Capacitated Location-Routing Problem," Service Science, INFORMS, vol. 53(1), pages 301-318, February.
    30. Jie, Wanchen & Yang, Jun & Zhang, Min & Huang, Yongxi, 2019. "The two-echelon capacitated electric vehicle routing problem with battery swapping stations: Formulation and efficient methodology," European Journal of Operational Research, Elsevier, vol. 272(3), pages 879-904.
    31. Nguyen, Viet-Phuong & Prins, Christian & Prodhon, Caroline, 2012. "Solving the two-echelon location routing problem by a GRASP reinforced by a learning process and path relinking," European Journal of Operational Research, Elsevier, vol. 216(1), pages 113-126.
    32. Schneider, M. & Stenger, A. & Goeke, D., 2014. "The Electric Vehicle Routing Problem with Time Windows and Recharging Stations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62382, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    33. Alexandra Anderluh & Rune Larsen & Vera C. Hemmelmayr & Pamela C. Nolz, 2020. "Impact of travel time uncertainties on the solution cost of a two-echelon vehicle routing problem with synchronization," Flexible Services and Manufacturing Journal, Springer, vol. 32(4), pages 806-828, December.
    34. Nagy, Gabor & Salhi, Said, 2005. "Heuristic algorithms for single and multiple depot vehicle routing problems with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 162(1), pages 126-141, April.
    35. Dan Liu & Zhenghong Deng & Qipeng Sun & Yong Wang & Yinhai Wang, 2019. "Design and Freight Corridor-Fleet Size Choice in Collaborative Intermodal Transportation Network Considering Economies of Scale," Sustainability, MDPI, vol. 11(4), pages 1-19, February.
    36. Renaud Masson & Fabien Lehuédé & Olivier Péton, 2013. "An Adaptive Large Neighborhood Search for the Pickup and Delivery Problem with Transfers," Transportation Science, INFORMS, vol. 47(3), pages 344-355, August.
    37. Soysal, Mehmet & Bloemhof-Ruwaard, Jacqueline M. & Bektaş, Tolga, 2015. "The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations," International Journal of Production Economics, Elsevier, vol. 164(C), pages 366-378.
    38. Jesus Gonzalez-Feliu & Guido Perboli & Roberto Tadei & Daniele Vigo, 2008. "The two-echelon capacitated vehicle routing problem," Working Papers halshs-00879447, HAL.
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