گسترشها و الگوریتمهای مساله مسیریابی وسیله نقلیه وسایل نقلیه آمیخته
محورهای موضوعی : آمارمجید یوسفی خوشبخت 1 , محمدرضا چهارمحالی 2
1 - گروه ریاضی، دانشکده علوم، دانشگاه بوعلیسینا، همدان، ایران
2 - گروه ریاضی، دانشکده علوم، دانشگاه بوعلیسینا، همدان، ایران
کلید واژه: Hard-NP problems, Depot, Vehicle Routing Problem, Fleet size and mix,
چکیده مقاله :
مساله مسیریابی وسیله نقلیه (VRP) یکی از مهمترین مسایل تحقیق در عملیات در صنایع و خدمات است که امروزه با توجه به هزینه بالای حمل و نقل در قیمت نهایی کالا، بسیار مورد توجه قرار میگیرد. از طرف دیگر با توجه به اینکه استفاده از وسایل نقلیه با ظرفیتهای گوناگون سبب کاهش بیشتر این هزینه میگردد، مسئله مسیریابی وسایل نقلیه آمیخته (FSMVRP) ارایه شد و از آن زمان، پیشرفت قابلتوجهی در مورد این مسائل و انواع آن در جهت استفاده در وسایل واقعی صورت گرفت. در این مساله، انواع مختلفی از وسایل نقلیه با ظرفیت متفاوت موجود در انبار کالای یکتا، برای خدمت به مجموعهای از مشتریان با موقعیتهای جغرافیایی شناخته شده، وجود دارند. به علاوه در این مسئله، هر یک از مشتریها به میزان خاصی کالا نیاز دارند که باید توسط ناوگانی ثابت از وسائل نقلیه به آنها تحویل گردد. هدف تعیین مجموعهای از تورها برای وسائل نقلیه با کمترین هزینه است به شرط آنکه هر وسیله نقلیه از انبار شروع به حرکت کرده و در انتها به آن بازگردد، هر مشتری دقیقاً یکبار توسط یک وسیله نقلیه بازدید شود و کل تقاضای مشتریهای هر تور از ظرفیت هر نوع از وسیله نقلیه، که 〖 q〗_iدر نظر گرفته میشود، تجاوز نکند. هدف این مقاله، طبقهبندی و بررسی مطالب مربوط به FSMVRP است. در این مقاله همچنین یک تحلیل مقایسهای از الگوریتمهای فراابتکاری برای این مساله ارائهشده است.
The vehicle routing problem (VRP) is one of the most important research issues in operations in industries and services, which is highly regarded today due to the high cost of transportation in the final price of goods. On the other hand, considering that the use of vehicles with different capacities will further reduce this cost, the issue of fleet size and mix vehicle routing (FSMVRP) was introduced and since then significant progress has been made on these issues and their types for use in Real tools were made. In this case, there are different types of vehicles with different capacities available in the unique depot to serve a group of customers with known geographical locations. In addition, in this case, each customer needs a certain amount of goods that must be delivered to them by a fixed fleet of vehicles. The goal is to determine the set of tours for the vehicles with the lowest cost, provided that: each vehicle starts from the depot and returns to it at the end, each customer is visited exactly once by one vehicle and the total customer demand of each tour exceeds the capacity do not exceed any type of vehicle, which is considered Qi. The purpose of this article is to categorize and review issues related to FSMVRP. This paper also provides a comparative analysis of meta-heuristic algorithms for these problems.
[1] M. Yousefikhoshbakht, F. Didehvar, and F. Rahmati, "An Effective rank based ant system algorithm for solving the balanced vehicle routing problem," International Journal of Industrial Engineering, vol. 23, no. 1, 2016.
[2] M. Yousefikhoshbakht, and M. Sedighpour, "An optimization algorithm for the capacitated vehicle routing problem based on ant colony system," Australian Journal of Basic and Applied Sciences, vol. 5, no. 12, pp.2729-2737, 2011.
[3] M. Ashouri, and M. Yousefikhoshbakht, "A Combination of Meta-heuristic and Heuristic Algorithms for the VRP, OVRP and VRP with Simultaneous Pickup and Delivery," BRAIN. Broad Research in Artificial Intelligence and Neuroscience, vol. 8, no. 2, pp.81-95, 2017.
[4] M. Yousefikhoshbakht, F. Didehvar, and F. Rahmati, " A mixed integer programming formulation for the heterogeneous fixed fleet open vehicle routing problem," Journal of optimization in Industrial Engineering, vol. 8, no. 18, pp.37-46, 2015.
[5] M. Yousefikhoshbakht, "Solving the traveling salesman problem: a modified metaheuristic algorithm," Complexity, pp.1-13, 2021.
[6] F. Maleki, and M. Yousefikhoshbakht, "A hybrid algorithm for the open vehicle routing problem," International Journal of Optimization in Civil Engineering, vol. 9, no. 2, pp.355-371, 2019.
[7] M. Yousefikhoshbakht, N. Malekzadeh, and M. Sedighpour, "Solving the traveling salesman problem based on the genetic reactive bone route algorithm with ant colony system," International Journal of Production Management and Engineering, vol 4, no. 2, pp.65-73, 2016.
[8] M.Yousefikhoshbakht,E. Mahmoodabadi, and M. Sedighpour, A modified elite ACO based avoiding premature convergence for traveling salesmen problem, vol. 7, no. 15, pp. 68-75, 2011.
[9] O. Bräysy et al., “An Effective Multirestart Deterministic Annealing Metaheuristic for the Fleet Size and Mix Vehicle-Routing Problem with Time Windows,” vol. 42, no. 3, pp. 371–386, 2016, doi: 10.1287/trsc.l070.0217.
[10] D. C. Paraskevopoulos, P. P. Repoussis, C. D. Tarantilis, G. Ioannou, and G. P. Prastacos, “A reactive variable neighborhood tabu search for the heterogeneous fleet vehicle routing problem with time windows,” Journal of Heuristics, vol. 14, no. 5, pp. 425–455, 2008, doi: 10.1007/s10732-007-9045-z.
[11] Ç. Koç, T. Bektaş, O. Jabali, and G. Laporte, “A hybrid evolutionary algorithm for heterogeneous fleet vehicle routing problems with time windows,” Computers and Operations Research, vol. 64, pp. 11–27, 2015, doi: 10.1016/j.cor.2015.05.004.
[12] R. Dondo and J. Cerdá, “A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows,” European Journal of Operational Research, vol. 176, no. 3, pp. 1478–1507,2007,doi:10.1016/j.ejor.2004.07.077.
[13] A. Bettinelli, A. Ceselli, and G. Righini, “A branch-and-cut-and-price algorithm for the multi-depot heterogeneous vehicle routing problem with time windows,” Transportation Research Part C: Emerging Technologies, vol. 19, no. 5, pp. 723–740, 2011, doi: 10.1016/j.trc.2010.07.008.
[14] A. Bettinelli, A. Ceselli, and G. Righini, “A branch-and-price algorithm for the multi-depot heterogeneous-fleet pickup and delivery problem with soft time windows,” Mathematical Programming Computation, vol. 6, no. 2, pp. 171–197, 2014, doi: 10.1007/s12532-014-0064-0.
[15] D. Teodorovic, E. Krcmar-Nozic, and G. Pavkovic, “The mixed fleet stochastic vehicle routing problem,” Transportation Planning & Technology, vol. 19, no. 1, pp. 31–43, 1995, doi: 10.1080/03081069508717556.
[16] S. Irnich, “Multi-depot pickup and delivery problem with a single hub and heterogeneous vehicles,” European Journal of Operational Research, vol. 122, no. 2, pp. 310–328, 2000, doi: 10.1016/S0377-2217(99)00235-0.
[17] Y. Qu and J. F. Bard, “A branch-and-price-and-cut algorithm for heterogeneous pickup and delivery problems with configurable vehicle capacity,” Transportation Science, vol. 49, no. 2, pp. 254–270, 2015, doi: 10.1287/trsc.2014.0524.
[18] C. Prins, “Engineering Applications of Artificial Intelligence Two memetic algorithms for heterogeneous fleet vehicle routing problems,” Engineering Applications of Artificial Intelligence, vol. 22, no. 6, pp. 916–928, 2009, doi: 10.1016/j.engappai.2008.10.006.
[19] M. P. Seixas and A. B. Mendes, “Column generation for a multitrip vehicle routing problem with time windows, driver work hours, and heterogeneous fleet,” Mathematical Problems in Engineering, vol. 2013, 2013, doi: 10.1155/2013/824961.
[20] C. W. Chu, “A heuristic algorithm for the truckload and less-than-truckload problem,” European Journal of Operational Research, vol. 165, no. 3, pp. 657–667, 2005, doi: 10.1016/j.ejor.2003.08.067.
[21] J. Y. Potvin and M. A. Naud, “Tabu search with ejection chains for the vehicle routing problem with private fleet and common carrier,” Journal of the Operational Research Society, vol. 62, no. 2, pp. 326–336, 2011, doi: 10.1057/jors.2010.102.
[22] F. Belmecheri, C. Prins, F. Yalaoui, and L. Amodeo, “Particle swarm optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows,” Journal of Intelligent Manufacturing, vol. 24, no. 4, pp. 775–789, 2013, doi: 10.1007/s10845-012-0627-8.
[23] S. Salhi, N. Wassan, and M. Hajarat, “The Fleet Size and Mix Vehicle Routing Problem with Backhauls: Formulation and Set Partitioning-based Heuristics,” Transportation Research Part E: Logistics and Transportation Review, vol. 56, pp. 22–35, 2013, doi: 10.1016/j.tre.2013.05.005.
[24] X. Li, S. C. H. Leung, and P. Tian, “A multistart adaptive memory-based tabu search algorithm for the heterogeneous fixed fleet open vehicle routing problem,” Expert Systems with Applications, vol. 39, no. 1, pp. 365–374, 2012, doi: 10.1016/j.eswa.2011.07.025.
[25] M. N. Kritikos and G. Ioannou, “The heterogeneous fleet vehicle routing problem with overloads and time windows,” International Journal of Production Economics, vol. 144, no. 1, pp. 68–75, 2013, doi: 10.1016/j.ijpe.2013.01.020.
[26] I. M. Chao, B. Golden, and E. Wasil, “A Computational study of a new heuristic for the site-dependent vehicle routing problem,” INFOR Journal, vol. 37 (O), no. 3, pp. 319–336, 1999, doi: 10.1080/03155986.1999.11732387.
[27] G. K. Rand, “Vehicle Routing: Methods and Studies (Studies in Management Science and Systems, Volume 16),” Journal of the Operational Research Society, vol. 39, no. 10, pp. 979–980, Oct. 1988, doi: 10.1057/jors.1988.167.
[28] M. Franceschelli, D. Rosa, C. Seatzu, and F. Bullo, “Gossip algorithms for heterogeneous multi-vehicle routing problems,” Nonlinear Analysis: Hybrid Systems, vol. 10, no. 1, pp. 156–174, 2013, doi: 10.1016/j.nahs.2013.03.001.
[29] A. A. Juan, J. Goentzel, and T. Bektas, “Routing fleets with multiple driving ranges : Is it possible to use greener fleet configurations ?,” vol. 21, pp. 84–94, 2014, doi: 10.1016/j.asoc.2014.03.012.
[30] Ç. Koç, T. Bektaş, O. Jabali, and G. Laporte, “The fleet size and mix pollution-routing problem,” Transportation Research Part B: Methodological, vol. 70, pp. 239–254, 2014, doi: 10.1016/j.trb.2014.09.008.
[31] M. Lai, T. G. Crainic, M. Di Francesco, and P. Zuddas, “An heuristic search for the routing of heterogeneous trucks with single and double container loads,” Transportation Research Part E: Logistics and Transportation Review, vol. 56, pp. 108–118, 2013, doi: 10.1016/j.tre.2013.06.001.
[32] O. Dominguez, A. A. Juan, B. Barrios, J. Faulin, and A. Agustin, “Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet,” Annals of Operations Research, vol. 236, no. 2, pp. 383–404, 2016, doi: 10.1007/s10479-014-1551-4.
[33] S. C. H. Leung, Z. Zhang, D. Zhang, X. Hua, and M. K. Lim, “A meta-heuristic algorithm for heterogeneous fleet vehicle routing problems with two-dimensional loading constraints,” European Journal of Operational Research, vol. 225, no. 2, pp. 199–210, 2013, doi: 10.1016/j.ejor.2012.09.023.
[34] B. Afshar-nadjafi, “ORIGINAL ARTICLE A constructive heuristic for time-dependent multi-depot vehicle routing problem with time-windows and heterogeneous fleet,” JOURNAL OF KING SAUD UNIVERSITY - ENGINEERING SCIENCES, 2014, doi: 10.1016/j.jksues. 2014.04.007.
[35] W. Qiang and W. Yuzhen, “Cluster synchronization of a class of multi-agent systems with a bipartite graph topology,” pp. 1–11, 2012, doi: 10.1007/s11432-012-4689-1.
[36] H. Larsen, “ECOLOGY OF HYPERSALINE ENVIRONMENTS,” pp. 23–39, 1946.
[37] B. Yao, B. Yu, P. Hu, and J. Gao, “An improved particle swarm optimization for carton heterogeneous vehicle routing problem with a collection depot,” 2015, doi: 10.1007/s10479-015-1792-x.
[38] R. Baldacci, M. Battarra, and D. Vigo, “Valid inequalities for the fleet size and mix vehicle routing problem with fixed costs,” Networks, vol. 54, no. 4, pp. 178–189, 2009, doi: 10.1002/net.20331.
[39] R. Baldacci, M. Battarra, and D. Vigo, “Valid Inequalities for the Fleet Size and Mix Vehicle Routing Problem with Fixed Costs,” 2009, doi: 10.1002/net.
[40] R. Baldacci and A. Mingozzi, “A unified exact method for solving different classes of vehicle routing problems,” Mathematical Programming, vol. 120, no. 2, pp. 347–380, 2009, doi: 10.1007/s10107-008-0218-9.
[41] H. Yaman, “Formulations and Valid Inequalities for the Heterogeneous,” vol. 390, pp. 365–390, 2006.
[42] C. E. Miller, S. Od, and S. Francisco, “Integer Programming Formulation of Traveling Salesman Problems *,” pp. 326–329, 1960.
[43] A. Pessoa, M. P. De Arag, and E. Uchoa, “A Robust Branch-Cut-and-Price Algorithm for the Heterogeneous Fleet Vehicle Routing Problem,” no. 0, pp. 150–160, 2007.
[44] E. Choi and D. Tcha, “A column generation approach to the heterogeneous fleet vehicle routing problem,” vol. 34, pp. 2080–2095, 2007, doi: 10.1016/j.cor.2005.08.002.
[45] R. Baldacci, E. Bartolini, A. Mingozzi, and R. Roberti, “An exact solution framework for a broad class of vehicle routing problems,” pp. 229–268, 2010, doi: 10.1007/s10287-009-0118-3.
[46] O. Jabali, M. Gendreau, and G. Laporte, “A continuous approximation model for the fleet composition problem,” TRANSPORTATION RESEARCH PART B, vol. 46, no. 10, pp. 1591–1606, 2012, doi: 10.1016/j.trb.2012.06.004.
[47] T. D. Traveled, A. A. Model, A. Author, C. F. D. Source, and I. S. Url,
Transportation Science,” vol. 18, no. 4, pp. 331–350, 2016.
[48] T. H. E. Length, O. F. Tours, and I. N. Zones, “The length of tours in zones different shapes?,” vol. 188, no. 2, pp. 135–145, 1984.
[49] G. F. Newell and C. F. Daganzo, “DESIGN OF MULTIPLE-VEHICLE DELIVERY A RING-RADIAL NETWORK TOURS-I,” no. 5, pp. 345–363, 1986.
[50] L. S. Ochi, D. S. Vianna, L. M. A. Drummond, and A. Victor, “A parallel evolutionary algorithm for the vehicle routing problem with heterogeneous fleet a,” no. 98, 1998.
[51] L. S. Ochi, D. S. Vianna, L. M. A. Drummond, and A. O. Victor, “An Evolutionary Hybrid Metaheuristic for Solving the Vehicle Routing Problem with Heterogeneous Fleet,” pp. 1–2.
[52] F. O. R. The and H. Fleet, “Communicated by Brian B,” vol. 33, no. September 1995, pp. 1–14, 1999.
[53] C. M. R. R. Lima, M. C. Goldbarg, and E. F. G. Goldbarg, “A Memetic Algorithm for the Heterogeneous Fleet Vehicle Routing Problem,” vol. 18, pp. 171–176, 2004, doi: 10.1016/j.endm.2004.06.027.
[54] I. H. Osman, “Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem,” vol. 41, pp. 421–451, 1993.
[55] B. Golden and F. Gheysens, “THE FLEET SIZE AND MIX VEHICLE ROUTING PROBLEM,” vol. I, no. I, 1982.
[56] S. Liu, W. Huang, and H. Ma, “An effective genetic algorithm for the fleet size and mix vehicle routing problems,” Transportation Research Part E, vol. 45, no. 3, pp. 434–445, 2009, doi: 10.1016/j.tre.2008.10.003.
[57] B. Jose, “A deterministic tabu search algorithm for the fleet size and mix vehicle routing problem,” vol. 195, pp. 716–728, 2009, doi: 10.1016/j.ejor.2007.05.059.
[58] C. Prins, “A simple and e ective evolutionary algorithm for the vehicle routing problem,” vol. 31, pp. 1985–2002, 2004, doi: 10.1016/S0305-0548(03)00158-8.
[59] T. Vidal, T. Gabriel, M. Gendreau, and C. Prins, “Discrete Optimization A unified solution framework for multi-attribute vehicle routing problems q,” European Journal of Operational Research, vol. 234, no. 3, pp. 658–673, 2014, doi: 10.1016/j.ejor.2013.09.045.
[60] “Unconfirmed 355670.crdownload.” .
[61] B. Birmingham and K. Rand, “Theory and Methodology Incorporating vehicle routing into the vehicle fleet composition problem *,” vol. 66, pp. 313–330, 1993.
[62] M. Gendreau, G. Laporte, C. Musaraganyi, and D. D. Taillard, “A tabu search heuristic for the heterogeneous # eet vehicle routing problem,” vol. 26, 1999.
[63] M. Gendreau, A. Hertz, and G. Laporte, “New Insertion and Postoptimization Procedures for the Traveling Salesman Problem,” no. September 2015, 1992.
[64] Y. Rochat, “Probabilistic Diversification and Intensification in Local Search for Vehicle Routing,” vol. 167, pp. 147–167, 1995.
[65] N. A. Wassan et al., “Tabu search variants for the mix fleet vehicle routing problem,” pp. 768–782, 2002.
[66] Y. H. Lee, J. I. Kim, K. H. Kang, and K. H. Kim, “A heuristic for vehicle fleet mix problem using tabu search and set partitioning,” pp. 833–841, 2008, doi: 10.1057/ palgrave.jors.2602421.
[67] G. Clarke and J. W. Wright, “Scheduling of Vehicles from a Central Depot to a Number of Delivery Points,” no. August 2015, 1964.
[68] M. L. Fisher and R. Jaikumar, “Generalized Assignment Heuristic for Vehicle Routing,” vol. 11, pp. 109–124, 1981.
[69] M. Vehicle and R. Problem, “ORSpekt m,” pp. 207–216, 1984.
[70] V. Routing and O. F. Size, “A N E W HEURISTIC FOR DETERMINING COMPOSITION FLEET SIZE AND Fi!ip G H E Y S E N S , Bruce G O L D E N and Arjang ASSAD,” vol. 26, pp. 233–236, 1986.
[71] “A NEW HEURISTIC FOR THE FLEET SIZE AND MIX VEHICLE ROUTING PROBLEM,” vol. 18, no. 3, pp. 263–274, 1991.
[72] S. Salhi, “Adaptation of Some Vehicle Fleet Mix Heuristics 1,” vol. 20, no. 5, pp. 653–660, 1992.
[73] J. Renaud and F. F. Boctor, “Discrete Optimization A sweep-based algorithm for the fleet size and mix vehicle routing problem,” vol. 140, pp. 618–628, 2002.
[74] C. O. Res and R. December, “Scope and,” vol. 23, no. 3, 1996.
[75] A. F. Han, “A GIDS METAHEURISTIC APPROACH TO THE FLEET SIZE AND MIX VEHICLE ROUTING PROBLEM.”
[76] “78.pdf.” .
[77] A. Imran, S. Salhi, and N. A. Wassan, “Discrete Optimization A variable neighborhood-based heuristic for the heterogeneous fleet vehicle routing problem,” European Journal of Operational Research, vol. 197, no. 2, pp. 509–518, 2009, doi: 10.1016/j.ejor.2008.07.022.
[78] A. Subramanian, P. Huachi, V. Penna, E. Uchoa, and L. Satoru, “Discrete Optimization A hybrid algorithm for the Heterogeneous Fleet Vehicle Routing Problem,” European Journal of Operational Research, vol. 221, no. 2, pp. 285–295, 2012, doi: 10.1016/j.ejor. 2012.03.016.
[79] P. Huachi, V. Penna, and A. Subramanian, “An Iterated Local Search heuristic for the Heterogeneous Fleet Vehicle Routing Problem,” 2011, doi: 10.1007/s10732-011-9186-y.
[80] J. A. Ferland and P. Michelon, “The Vehicle Scheduling Problem with Multiple Vehicle Types,” vol. 39, no. 6, pp. 577–583, 2013.
[81] R. Emilia, V. Amendola, R. Emilia, M. D. Amico, and D. Vigo, “Heuristic Approaches for the Fleet Size and Mix Vehicle Routing Problem with Time Windows,” vol. 41, no. 4, pp. 516–526, 2007, doi: 10.1287/trsc.1070.0190.
[82] “No Title,” vol. 12, no. 4, pp. 568–581, 2013.
[83] B. Vernimmen, W. Dullaert, and K. So, “New heuristics for the Fleet Size and Mix Vehicle Routing Problem with Time Windows,” pp. 1232–1238, 2002.
[84] P. P. Repoussis and C. D. Tarantilis, “Solving the Fleet Size and Mix Vehicle Routing Problem with Time Windows via Adaptive Memory Programming,” Transportation Research Part C, vol. 18, no. 5, pp. 695–712, 2010, doi: 10.1016/j.trc.2009.08.004.
[85] O. Bräysy, P. P. Porkka, W. Dullaert, P. P. Repoussis, and C. D. Tarantilis, “A well-scalable metaheuristic for the fleet size and mix vehicle routing problem with time windows,” Expert Systems with Applications, vol. 36, no. 4, pp. 8460–8475, 2009, doi: 10.1016/j.eswa.2008.10.040.
[86] A. Prieto, F. Bellas, P. Caamaño, and R. J. Duro, “Solving a heterogeneous fleet vehicle routing problem with time windows through the asynchronous situated coevolution algorithm,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5778 LNAI, no. PART 2, pp. 200–207, 2011, doi: 10.1007/978-3-642-21314-4_25.
[87] S. Ceschia, L. Di, and G. Andrea, “Tabu search techniques for the heterogeneous vehicle routing problem with time windows and carrier-dependent costs,” pp. 601–615, 2011, doi: 10.1007/s10951-010-0213-x.
[88] M. C. Bolduc, J. Renaud, and F. Boctor, “A heuristic for the routing and carrier selection problem,” European Journal of Operational Research, vol. 183, no. 2, pp. 926–932, 2007, doi: 10.1016/j.ejor.2006.10.013.
[89] N. Safaei and Y. Gholipour, “A hybrid simulated annealing for capacitated vehicle routing problems with the independent route length,” vol. 176, pp. 445–454, 2006, doi: 10.1016/j.amc.2005.09.040.
[90] V. Yepes, J. Medina, and M. Asce, “for Heterogeneous Fleet VRPHESTW,” vol. c, no. April, pp. 303–311, 2006.
[91] J. J. De, C. Carlos, and V. C. J. R. Montoya-torres, “A two-pheromone trail ant colony system — tabu search approach for the heterogeneous vehicle routing problem with time windows and multiple products,” pp. 233–252, 2013, doi: 10.1007/s10732-011-9184-0.
[92] G. Barbarosoglu and D. Ozgur, “A tabu search algorithm for the vehicle routing problem,” vol. 26, no. October 1997, 1999.
[93] J. Homberger and H. Gehring, “Two Evolutionary Metaheuristics For The Vehicle Routing Problem With Time Windows TWO EVOLUTIONARY METAHEURISTICS FOR THE VEHICLE ROUTING PRaBLEM WITH TIME WINDOWS !,” vol. 5986, no. June, 2016, doi: 10.1080/03155986.1999.11732386.
[94] W. Dullaert, G. K. Janssens, and B. Vemimmen, “New heuristics for the Fleet Size and Mix Vehicle Routing Problem with Time Windows,” vol. 53, no. 11, pp. 1232–1238, 2014, doi: 10.1057/palgrave.jors.2601422.
[95] J. Jiang, K. M. Ng, K. L. Poh, and K. M. Teo, “Expert Systems with Applications Vehicle routing problem with a heterogeneous fleet and time windows,” EXPERT SYSTEMS WITH APPLICATIONS, vol. 41, no. 8, pp. 3748–3760, 2014, doi: 10.1016/j.eswa.2013.11.029.
[96] H. C. Lau, M. Sim, and K. M. Teo, “Vehicle routing problem with time windows and a limited number of vehicles,” vol. 148, pp. 559–569, 2003, doi: 10.1016/S0377-2217(02)00363-6.
[97] H. I. Calvete and C. Gale, “A goal programming approach to vehicle routing problems with soft time windows q,” vol. 177, pp. 1720–1733, 2007, doi: 10.1016/j.ejor.2005.10.010.
[98] H. Tsugunobu and Y. Yoshizaki, “Scatter search for a real-life heterogeneous fleet vehicle routing problem with time windows and split deliveries in Brazil,” vol. 199, pp. 750–758, 2009, doi: 10.1016/j.ejor.2008.08.003.
[99] S. C. Ho and D. Haugland, “A tabu search heuristic for the vehicle routing problem with time windows and split deliveries,” vol. 31, pp. 1947–1964, 2004, doi: 10.1016/S0305-0548(03)00155-2.
[100] Y. Xu and L. Wang, “K-nearest neighbor-based weighted twin support vector regression,” 2014, doi: 10.1007/s10489-014-0518-0.
[101] G. Laporte, “Heuristics for the Vehicle Routing Problem,” pp. 87–116.