RESEARCH ON OPTIMISATION OF COUNTY-LEVEL URBAN EXPRESS DELIVERY USING A MULTI-STRATEGY IMPROVED GENETIC ALGORITHM

Hongjun Zhu, Yangxin Teng, and Shuchang Xiao

References

  1. [1] H. Buchel and S. Spinler, The impact of the metaverse one-commerce business models—A delphi-based scenario study,Technology in Society, 76, 2024, 102465.
  2. [2] L. Janinhoff, R. Klein, D. Sailer, and J. M. Schoppa, Out-of-home delivery in last-mile logistics: A review, Computers &Operations Research, 168, 2024, 106686.
  3. [3] H.-W. Lee, S. Ahmed, and C.-S. Lee, Research on pathplanning of logistics intelligent unmanned aerial vehicle,International Journal of Robotics and Automation, 39(6), 2024,450–463.
  4. [4] M. Kaspi, T. Raviv, and M. W. Ulmer, Directions for futureresearch on urban mobility and city logistics, Networks, 79(3),2022, 253–263.
  5. [5] S. Pelletier, O. Jabali, and G. Laporte, 50th anniversary invitedarticle—Goods distribution with electric vehicles: Review andresearch perspectives, Transportation Science, 50(1), 2016,3–22.
  6. [6] K. Aljohani and R. G. Thompson, Impacts of logistics sprawl onthe urban environment and logistics: Taxonomy and review ofliterature, Journal of Transport Geography, 57, 2016, 255–263.
  7. [7] A. Comi, G. Fancello, F. Piras, and P. Serra, Towardsmore sustainable cities: Tools and policies for urban goodsmovements, Journal of Advanced Transportation, 2024(1),2024, 1952969.
  8. [8] H. Ma, Y. Zhang, S. Sun, T. Liu, and Y. Shan, A comprehensivesurvey on NSGA-II for multi-objective optimization andapplications, Artificial Intelligence Review, 56(12), 2023,15217–15270.
  9. [9] T. Feng, J. Li, H. Jiang, S. X. Yang, P. Wang, Y. Teng, S.Chen, Q. Fu, and B. Luo, The optimal global path planningof mobile robot based on improved hybrid adaptive geneticalgorithm in different tasks and complex road environments,IEEE Access, 12, 2024, 18400–18415.
  10. [10] H. Liu, L. Zhang, B. Zhao, J. Tang, J. Luo, and S. Wang,Research on emergency scheduling based on improved geneticalgorithm in harvester failure scenarios, Frontiers in PlantScience, 15, 2024, 1413595.
  11. [11] G. B. Dantzig and J. H. Ramser, The truck dispatchingproblem, Management Science, 6(1), 1959, 80–91.15
  12. [12] G. Clarke and J. W. Wright, Scheduling of vehicles froma central depot to a number of delivery points, OperationsResearch, 12(4), 1964, 568–581.
  13. [13] M. Desrochers, J. Desrosiers, and M. Solomon, A newoptimization algorithm for the vehicle routing problem withtime windows, Operations Research, 40(2), 1992, 342–354.
  14. [14] J. Wang, Y. Zhou, Y. Wang, J. Zhang, C. P. Chen, and Z. Zheng,Multiobjective vehicle routing problems with simultaneousdelivery and pickup and time windows: Formulation, instances,and algorithms, IEEE Transactions on Cybernetics, 46(3),2015, 582–594.
  15. [15] A. Garcia-Najera and A. Lopez-Jaimes, An investigationinto many-objective optimization on combinatorial problems:Analyzing the pickup and delivery problem, Swarm andEvolutionary Computation, 38, 2018, 218–230.
  16. [16] Y. Yao, X. Zhu, H. Dong, S. Wu, H. Wu, L. C. Tong, and X.Zhou, ADMM-based problem decomposition scheme for vehiclerouting problem with time windows, Transportation ResearchPart B: Methodological, 129, 2019, 156–174.
  17. [17] A. Amiri, H. Zolfagharinia, and S. H. Amin, Routing a mixedfleet of conventional and electric vehicles for urban deliveryproblems: Considering different charging technologies andbattery swapping, International Journal of Systems Science:Operations & Logistics, 10(1), 2023, 2191804.
  18. [18] S. Iqbal, M. Kaykobad, and M. S. Rahman, Solving the multi-objective vehicle routing problem with soft time windows withthe help of bees. Swarm and Evolutionary Computation, 24,2015, 50–64.
  19. [19] G. Srivastava, A. Singh, and R. Mallipeddi, NSGA-II withobjective-specific variation operators for multiobjective vehiclerouting problem with time windows, Expert Systems withApplications, 176, 2021, 114779.
  20. [20] P. Jiang, J. Men, H. Xu, S. Zheng, Y. Kong, and L. Zhang,A variable neighborhood search-based hybrid multi objectiveevolutionary algorithm for HazMat heterogeneous vehiclerouting problem with time windows, IEEE Systems Journal,14(3), 2020, 4344–4355.
  21. [21] D. Goeke and M. Schneider, Routing a mixed fleet of electricand conventional vehicles, European Journal of OperationalResearch, 245(1), 2015, 81–99.
  22. [22] X. Ren, H. Huang, S. Feng, and G. Liang, An improved variableneighborhood search for bi-objective mixed-energy fleet vehiclerouting problem, Journal of Cleaner Production, 275, 2020,124155.
  23. [23] S. Erdogan and E. Miller-Hooks, A green vehicle routingproblem, Transportation Research Part E: Logistics andTransportation Review, 48(1), 2012, 100–114.
  24. [24] M. E. H. Sadati and B. C¸atay, A hybrid variable neighborhoodsearch approach for the multi-depot green vehicle routingproblem, Transportation Research Part E: Logistics andTransportation Review, 149, 2021, 102293.
  25. [25] M. Schneider, A. Stenger, and D. Goeke, The electric vehicle-routing problem with time windows and recharging stations,Transportation Science, 48(4), 2014, 500–520.
  26. [26] M. Avci and S. Topaloglu, A hybrid metaheuristic algorithmfor heterogeneous vehicle routing problem with simultaneouspickup and delivery, Expert Systems With Applications, 53,2016, 160–171.
  27. [27] J. Li, P. M. Pardalos, H. Sun, J. Pei, and Y. Zhang, Iterated localsearch embedded adaptive neighborhood selection approachfor the multi-depot vehicle routing problem with simultaneousdeliveries and pickups, Expert Systems with Applications, 42(7),2015, 3551–3561.
  28. [28] O. S. Da Silva J´unior, J. E. Leal, and M. Reimann, A multipleant colony system with random variable neighborhood descentfor the dynamic vehicle routing problem with time windows,Soft Computing, 25(4), 2021, 2935–2948.
  29. [29] Y. Wu and M. Jian, State aggregation and lower bound-based ADP approach for dynamic pick-up routing problemwith capacity constraint, IEEE Transactions on IntelligentTransportation Systems, 25, 2024, 9932–9944.
  30. [30] Y. Wu, B. Zeng, and M. Jian, ADP- and rollout-baseddynamic vehicle routing for pick-up service via budgetingcapacity, Flexible Services and Manufacturing Journal, 37,2024, 513–557.
  31. [31] V. Pillac, M. Gendreau, C. Gueret, and A. L. Medaglia, Areview of dynamic vehicle routing problems, European Journalof Operational Research, 225(1), 2013, 1–11.
  32. [32] M. Li, J. Lu, and W. Ma, A hybrid multi-objective geneticalgorithm for bi-objective time window assignment vehiclerouting problem, Promet-Traffic&Transportation, 31(5), 2019,513–525.
  33. [33] A. Eydi and S. A. Ghasemi-Nezhad, A bi-objective vehiclerouting problem with time windows and multiple demands,Ain Shams Engineering Journal, 12(3), 2021, 2617–2630.
  34. [34] A. A. Kovacs, B. L. Golden, R. F. Hartl, and S. N. Parragh,Vehicle routing problems in which consistency considerationsare important: A survey, Networks, 64(3), 2014, 192–213.
  35. [35] D. Sariklis and S. Powell, A heuristic method for the openvehicle routing problem, Journal of the Operational ResearchSociety, 51(5), 2000, 564–573.
  36. [36] E. Dasdemir, M. C. Testik, D. T. ¨Ozt¨urk, C. T. S¸akar, G.G¨ulery¨uz, and O. M. Testik, A multi-objective open vehiclerouting problem with overbooking: Exact and heuristic solutionapproaches for an employee transportation problem, Omega,108, 2022, 102587.
  37. [37] D. Gasset, F. Paillalef, S. Payacan, G. Gatica, G. Herrera-Vidal,R. Linfati, and J. R. Coronado-Hernandez, Route optimizationfor open vehicle routing problem (OVRP): A mathematicaland solution approach, Applied Sciences, 14(16), 2024, 6931.
  38. [38] R. Tyasnurita, E. Ozcan, J. H. Drake, and S. Asta, Constructingselection hyper-heuristics for open vehicle routing with timedelay neural networks using multiple experts, Knowledge-BasedSystems, 295, 2024, 111731.
  39. [39] M. Jepsen, S. Spoorendonk, and S. Ropke, A branch-and-cutalgorithm for the symmetric two-echelon capacitated vehiclerouting problem, Transportation Science, 47(1), 2013, 23–37.
  40. [40] Y. Wang, S. Peng, X. Guan, J. Fan, Z. Wang, Y. Liu, and H.Wang, Collaborative logistics pickup and delivery problem witheco-packages based on time–space network, Expert Systemswith Applications, 170, 2021, 114561.
  41. [41] N. Dellaert, F. Dashty Saridarq, T. Van Woensel, and T. G.Crainic, Branch-and-price–based algorithms for the two-echelonvehicle routing problem with time windows, TransportationScience, 53(2), 2019, 463–479.
  42. [42] M. Casazza, A. Ceselli, and R. W. Calvo, A route decompositionapproach for the single commodity split pickup and splitdelivery vehicle routing problem, European Journal ofOperational Research, 289(3), 2021, 897–911.
  43. [43] M. Casazza, A. Ceselli, D. Chemla, F. Meunier, and R. WolflerCalvo, The multiple vehicle balancing problem, Networks,72(3), 2018, 337–357.
  44. [44] D. Dumez, C. Tilk, S. Irnich, F. Lehuede, and O. Peton,Hybridizing large neighborhood search and exact methods forgeneralized vehicle routing problems with time windows, EUROJournal on Transportation and Logistics, 10, 2021, 100040.
  45. [45] F. Senna, L. C. Coelho, R. Morabito, and P. Munari,An exact method for a last-mile delivery routing problemwith multiple deliverymen, European Journal of OperationalResearch, 317(2), 2024, 550–562.
  46. [46] D. Cvijovic and J. Klinowski, Taboo search: An approach to themultiple minima problem, Science, 267(5198), 1995, 664–666.
  47. [47] K.Gao, Z. Cao, L. Zhang, Z. Chen, Y. Han, and Q. Pan,A review on swarm intelligence and evolutionary algorithmsfor solving flexible job shop scheduling problems, IEEE/CAAJournal of Automatica Sinica, 6(4), 2019, 904–916.
  48. [48] T. Liu, J. Li, S. X. Yang, Z. Gong, Z. li Liu, H. Zhong, andQ. Fu, Optimal coverage path planning for tractors in hillyareas based on energy consumption model, 20-31, InternationalJournal of Robotics and Automation, 38(1). 2023, 20–31.
  49. [49] A. M. Fathollahi-Fard, K. Y. Wong, and M. Aljuaid, Anefficient adaptive large neighborhood search algorithm basedon heuristics and reformulations for the generalized quadraticassignment problem, Engineering Applications of ArtificialIntelligence, 126, 2023, 106802.
  50. [50] W. Jie, J. Yang, M. Zhang, and Y. Huang, The two-echeloncapacitated electric vehicle routing problem with batteryswapping stations: Formulation and efficient methodology,European Journal of Operational Research, 272(3), 2019,879–904.16
  51. [51] D. Wang and H. Zhou, A two-echelon electric vehicle routingproblem with time windows and battery swapping stations,Applied Sciences, 11(22), 2021, 10779.
  52. [52] J. Cai, Q. Zhu, Q. Lin, Z. Ming, and K. C. Tan, Decomposition-based multiobjective evolutionary optimization with tabusearch for dynamic pickup and delivery problems, IEEETransactions on Intelligent Transportation Systems, 25, 2024,14830–14843.
  53. [53] H. Wu and Y. Gao, An ant colony optimization based onlocal search for the vehicle routing problem with simultaneouspickup–delivery and time window, Applied Soft Computing,139, 2023, 110203.
  54. [54] S. Mu, B. Liu, G. Jijian, C. Lien, and C. Xiaojie, Analyzingvehicle path optimization using an improved genetic algorithmin the presence of stochastic perturbation matter, ScientificReports, 14(1), 2024, 26105.
  55. [55] H. Karmouni, T. Jahid, A. Hmimid, M. Sayyouri, and H. Qjidaa,Fast computation of inverse Meixner moments transformusing Clenshaw’s formula, Multimedia Tools and Applications,78(22), 2019, 31245–31265.
  56. [56] H. Karmouni, A. Hmimid, T. Jahid, M. Sayyouri, H. Qjidaa,and A. Rezzouk, Fast and stable computation of the charliermoments and their inverses using digital filters and image blockrepresentation, Circuits Systems and Signal Processing, 37(9),2018, 4015–4033.
  57. [57] H. Karmouni, M. Yamni, O. ElOgri, A, Daoui, M. Sayyouri, andH. Qjidaa, Fast computation of 3D discrete invariant momentsbased on 3D cuboid for 3D image classification, Circuits Systemsand Signal Processing, 40(8), 2021, 3782–3812.
  58. [58] B. Nie, Y. Gao, Y. Mei, and F. Gao, Fast capability iterationnetwork for robot path planning, International Journal ofRobotics and Automation, 37(3), 2022, 266–272.

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