A new working mode of overloaded traffic control for rural highways is presented, and a location-routing model is built to optimize the check base distribution and the control vehicles’ routing schemes. Then, for the location-routing model with a large set of location alternatives and an unknown settable number of check bases, a multiple ant colony optimization algorithm is designed to solve the model. Furthermore, actual data from Guiyang rural highways are used to perform a numerical analysis. The results indicate that the model can be used to obtain the optimal base location-vehicle routing scheme to verify the feasibility of the model and the algorithm. The model and algorithm can help managers to make decisions on locating the check bases and routing the control vehicles.
Zeng FQ, Huang XM. Asphalt pavement stress under overloading. Journal of Traffic and Transportation Engineering. 2004;4(3): 8-10.
Li L, Wu QQ. Research on countermeasures of long-term oversize and overload controlling base on relational interest factors. Journal of Highway and Transportation Research and Development. 2008;25(3): 153-158.
Bagui, Das A, Bapanapalli C. Controlling Vehicle Overloading in BOT Projects. Procedia - Social and Behavioral Sciences. 2013;104(2): 962-971.
Moreno-Quintero E, Fowkes T, Watling D. Modelling planner–carrier interactions in road freight transport: Optimisation of road maintenance costs via overloading control. Transportation Research Part E: Logistics & Transportation Review. 2013;50(1): 68-83.
Li ZK, Rong ZH. Research on long term solution mechanism and countermeasure to overload and oversize transportation of highway. China Journal of Highway and Transport. 2005;18(4): 96-99.
Chen YS. Long-term effective solution to the overload transportation with economic lever. China Journal of Highway and Transport. 2004;17(02): 95-100.
Salhi S, Rand GK. The effect of ignoring routes when locating depots. European Journal of Operational Research. 1989;39(2): 150-156.
Nagy G, Salhi S. Location-routing: Issues, models and methods. European Journal of Operational Research. 2007;177(2): 649-72.
Luo YB, Sun YM. Capacitated Location routing problem based on fuzzy time windows. Systems Engineering. 2014;32(01): 19-25.
Nadizadeh A, Hosseini Nasab H. Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm. European Journal of Operational Research. 2014;238(2): 458-70.
Cheng XQ, Jia JT, Li Y, Liu XW. Bi-level programming and algorithm on the location of arterial highway management station. Journal of Transportation Systems Engineering and Information Technology. 2016;16(3): 207-213.
Caballero R, Mercedes González, Guerrero FM, et al. Solving a multiobjective location routing problem with a metaheuristic based on tabu search. Application to a real case in Andalusia. European Journal of Operational Research. 2007;177(3): 1751-63.
Zhao J, Verter V. A bi-objective model for the used oil location-routing problem. Computers & Operations Research. 2014; 62.
Govindan K, Jafarian A, Khodaverdi R, Devika K. 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. 2014;152(2): 9-28.
Sun QW, Zhang Y. Study on Location-routing Problem with Simultaneous Pickup and Delivery. Journal of Transportation Engineering and Information. 2017;15(2): 100-104.
Laporte G, Nobert Y. An exact algorithm for minimizing routing and operating costs in depot location. European Journal of Operational Research. 1981;6(2): 224-226.
Laporte G, Nobert Y, Taillefer S. Solving a Family of Multi-Depot Vehicle Routing and Location-Routing Problems. Transportation Science. 1988;22(3): 161-172.
Akca Z, Berger RT, Ralphs TK. A branch-and-price algorithm for combined location and routing problems under capacity restrictions. Operations Research/Computer Science Interfaces. 2009;47: 309-330.
Srivastava R. Alternate solution procedures for the location-routing problem. Omega. 1993;21(4): 497-506.
Murty KG, Djang PA. The U.S. Army National Guard's Mobile Training Simulators Location and Routing Problem. Operations Research. 1999;47(2):175-182.
Balakrishnan A, Ward JE, Wong RT. Integrated facility location and vehicle routing models: Recent work and future prospects. American Journal of Mathematical and Management Sciences. 1987;7(1-2): 35-61.
Salhi S, Nagy G. Consistency and robustness in location-routing. Studies in Locational Analysis. 1999;13(3): 3-19.
Srivastava R, Benton WC. The location-routing problem: Considerations in physical distribution system design. Computers & Operations Research. 1990;17(5):427-435.
Barreto S, Ferreira C, Paixão J, Santos BS. Using clustering analysis in a capacitated location-routing problem. European Journal of Operational Research. 2007;179(3): 968-977.
Wu TH, Low C, Bai JW. Heuristic solutions to multi-depot location-routing problems. Computers & Operations Research. 2002;29(10): 1393-1415.
Salhi GN. Nested heuristic methods for the location-routeing problem. The Journal of the Operational Research Society. 1996;47(9): 1166-1174.
Nambiar JM, Gelders LF, Wassenhove LNV. A large scale location-allocation problem in the natural rubber industry. European Journal of Operational Research. 1981;6(2): 183-189.
Albareda-Sambola M, Dı́az JA, Fernández E. A compact model and tight bounds for a combined location-routing problem. Computers & Operations Research. 2005;32(3): 407-428.
Bouhafs L, Hajjam A, Koukam A. A Combination of Simulated Annealing and Ant Colony System for the Capacitated Location-Routing Problem. Knowledge-based Intelligent Information & Engineering Systems, International Conference, Kes, Bournemouth, Uk, October, Part I. Springer-Verlag; 2006.
Marinakis Y, Marinaki M. A Bilevel Genetic Algorithm for a real life location routing problem. International Journal of Logistics Research & Applications. 2008;11(1): 49-65.
Yu B, Jin PH, Yang ZZ. Two-stage heuristic algorithm for multi-depot vehicle routing problem with time windows. Systems Engineering - Theory & Practice. 2012;32(8): 1793-1800.
Dorigo M, Maniezzo V, Colorni A. Ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics. 1996;26(1): 29-41.
Yao BZ, Hu P, Zhang MH, Tian XM. Improved ant colony optimization for seafood product delivery routing problem. Promet – Traffic&Transportation. 2014;26(1): 1-10.
Yu B, Yang ZZ, Yao BZ. An improved ant colony optimization for vehicle routing problem. European Journal of Operational Research. 2009;196(1): 171-176.
Gambardella LM, Taillard R, Agazzi G. MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with Time Windows. New Ideas in Optimization. 1999; 63-76.
Ting CJ, Chen CH. A multiple ant colony optimization algorithm for the capacitated location routing problem. International Journal of Production Economics. 2013;141(1): 34-44.
Ma JH, Fang Y, Yuan J. Mutation ant colony algorithm for multiple-depot multiple-types vehicle routing problems with shortest finish time. Systems Engineering - Theory and Practice. 2011;31(8): 1508-1516.
Dorigo M, Stützle T. Ant Colony Optimization. IEEE; 2004.
He YZ, Yang ZZ. Optimization of express distribution by cooperatively using private trucks and buses. Journal of Traffic and Transportation Engineering. 2017;17(6): 97-103.
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