Relevant bibliographies by topics / Vehicle routing and scheduling

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Vehicle routing and scheduling'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Vehicle routing and scheduling"

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Laporte, Gilbert. "Scheduling issues in vehicle routing." Annals of Operations Research 236, no. 2 (July 13, 2013): 463–74. http://dx.doi.org/10.1007/s10479-013-1423-3.

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Lam, Edward, Pascal Van Hentenryck, and Phil Kilby. "Joint Vehicle and Crew Routing and Scheduling." Transportation Science 54, no. 2 (March 2020): 488–511. http://dx.doi.org/10.1287/trsc.2019.0907.

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Traditional vehicle routing problems implicitly assume that only one crew operates a vehicle for the entirety of its journey. However, this assumption is violated in many applications arising in humanitarian and military logistics. This paper considers a joint vehicle and crew routing and scheduling problem in which crews are able to interchange vehicles, resulting in space and time interdependencies between vehicle routes and crew routes. The problem is formulated as a mixed integer programming (MIP) model and a constraint programming (CP) model that overlay crew routing constraints over a standard vehicle routing problem. The constraint program uses a novel optimization constraint to detect infeasibility and to bound crew objectives. This paper also explores methods using large neighborhood search over the MIP and CP models. Experimental results indicate that modeling the vehicle and crew routing problems jointly and supporting vehicle interchanges for crews may bring significant benefits in cost reduction compared with a method that sequentializes these decisions.
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Arunapuram, Sundararajan, Kamlesh Mathur, and Daniel Solow. "Vehicle Routing and Scheduling with Full Truckloads." Transportation Science 37, no. 2 (May 2003): 170–82. http://dx.doi.org/10.1287/trsc.37.2.170.15248.

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Golden, Bruce L., Lawrence Bodin, and Terry Goodwin. "Microcomputer-based vehicle routing and scheduling software." Computers & Operations Research 13, no. 2-3 (January 1986): 277–85. http://dx.doi.org/10.1016/0305-0548(86)90012-2.

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Bott, Kevin, and Ronald H. Ballou. "Research perspectives in vehicle routing and scheduling." Transportation Research Part A: General 20, no. 3 (May 1986): 239–43. http://dx.doi.org/10.1016/0191-2607(86)90097-x.

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LU, Mingzhe, Hiroshi KISE, Yoshiyuki KARUNO, and Toshio OHKAWA. "Routing and Scheduling for Permutation Circulation-Type Vehicle Routing System." Transactions of the Japan Society of Mechanical Engineers Series C 68, no. 673 (2002): 2833–39. http://dx.doi.org/10.1299/kikaic.68.2833.

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Zou, Hao, and Tiantian Zhang. "Research on Vehicle Routing Algorithm for Supply Chain Logistics Distribution." MATEC Web of Conferences 227 (2018): 02003. http://dx.doi.org/10.1051/matecconf/201822702003.

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In view of logistics distribution vehicle scheduling problem, this paper proposes a vehicle routing optimization model considering route and time. Secondly, the vehicle routing optimization model is designed in detail, and the mathematical derivation steps are given, and the decision-making process of this problem is simulated with data. Finally, the paper takes the route of logistics distribution vehicles as the goal, and makes a preliminary verification. The results show that the algorithm is conducive to improving the management efficiency of the whole supply chain.
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Tung, Dang Vu, and Anulark Pinnoi. "Vehicle routing–scheduling for waste collection in Hanoi." European Journal of Operational Research 125, no. 3 (September 2000): 449–68. http://dx.doi.org/10.1016/s0377-2217(99)00408-7.

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Lysgaard, Jens. "Dynamic Transportation Networks in Vehicle Routing and Scheduling." Interfaces 22, no. 3 (June 1992): 45–55. http://dx.doi.org/10.1287/inte.22.3.45.

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Goel, Asvin. "Vehicle Scheduling and Routing with Drivers' Working Hours." Transportation Science 43, no. 1 (February 2009): 17–26. http://dx.doi.org/10.1287/trsc.1070.0226.

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Dissertations / Theses on the topic "Vehicle routing and scheduling"

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Mu, Qianxin. "Disruption management in vehicle routing and scheduling." Thesis, Lancaster University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.543984.

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Arunapuram, Sundararajan. "Vehicle routing and scheduling with full loads." Case Western Reserve University School of Graduate Studies / OhioLINK, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=case1056646152.

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Eibl, Peter G. "Computerised vehicle routing and scheduling in brewery distribution." Thesis, University of South Wales, 1995. https://pure.southwales.ac.uk/en/studentthesis/computerised-vehicle-routing-and-scheduling-in-brewery-distribution(65ecb5ac-c789-4ead-a72a-2605371ca202).html.

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Over the past twenty years academics, industry commentators and practitioners in the field of physical distribution have been pre-occupied with the computational and technical side of computerised vehicle routing and scheduling (CVRS). Comparatively little research activity has been carried out on the user or management aspects of the technology. The current study aims to make up for this research deficit by investigating the adoption of CVRS technology in the British road freight industry. Moreover, the study evaluates the success of the software used in a strategic, tactical and operational role. The subject of the empirical analyses is the British brewing industry. The findings highlight the fact that CVRS technology is used by only a relatively small number of organisations despite being an effective means to improve the efficiency of transport operations and to provide substantial intangible benefits. The research also develops and empirically validates a model of CVRS in the organisational context. "Organisational context" means that the focus is on the organisational aspects rather than on the technical aspects of the technology. The model investigates relationships between variables and addresses two major research questions: What are the reasons leading to the apparent lack of CVRS system penetration - the "CVRS user-gap"? What are the key factors of successful implementations and subsequent use of the software? To overcome the "CVRS user-gap", the study suggests appropriate measures focusing on individuals' awareness of and attitudes towards the software rather than on improving the quality of the software. To ensure CVRS success, the potential users of CVRS should have a certain level of technological and organisational maturity. Emphasis needs to be placed on adequate system implementation. Special attention should also be given to three critical success factors: the quality of the software; the system operator's ability to use the software; and the drivers willingness and ability to adhere to the computer-generated route proposals.
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Kenyon, Astrid Sandrine. "Stochastic vehicle routing problems with random travel times /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Gurumurthy, Prakash. "Dynamic stochastic vehicle routing model in home healthcare scheduling /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p1426064.

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Gutierrez, Bonilla Andres Felipe. "Maintenance Scheduling and Vehicle Routing Optimisation with Stochastic Components." Thesis, Troyes, 2018. http://www.theses.fr/2018TROY0023.

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Cette thèse est dédiée aux problèmes de tournées de véhicules stochastiques (SVRP) abordés dans un contexte de planification de tâches de maintenance. Le paradigme de solutions À Priori est choisi pour inclure les incertitudes au moment de la planification. Deux SVRP sont étudiés, d’abord le problème avec demandes stochastiques, qui est résolu par un algorithme mémétique (MA) hybridé avec une procédure de recherche adaptative randomisée. La méthode s’est montrée compétitive en comparaison à d’autres approches disponibles dans la littérature. Ensuite le SVRP avec fenêtre de temps sur le service, et temps de trajets et de services stochastiques est considéré. Un algorithme mémétique parallèle est conçu pour le résoudre efficacement. Un troisième problème traitant de l’ordonnancement de la maintenance pour un parc d’éoliennes est étudié dans cette thèse. D’abord une version déterministe et bi-objective est modélisée sous forme d’un programme linéaire à variables mixtes, puis résolue par une méthode de type epsilon contraintes. Une extension du problème sur un horizon de planification long et considérant les stratégies de maintenance est également proposée, et le problème est résolu par une méthode basée sur la simulation. Les méthodes développées mettent en évidence, pour les deux derniers problèmes, le conflit entre la minimisation des coûts de maintenance et la maximisation de la production énergétique
This thesis studies Stochastic Vehicle Routing Problems (SVRPs) in the context of maintenance tasks scheduling. Stochastic programming under an A Priori paradigm is used to incorporate the uncertainties. Two SVRPs are addressed, the first one deals with Stochastic Demands which is solved by a hybrid approach combining a memetic algorithm (MA) and a Greedy Randomized Adaptive Search Procedure (GRASP). The designed hybrid method is shown to be competitive compared to other published approaches. Second, the SVRP with stochastic travel and service times and hard time windows investigated. A parallel Memetic Algorithm is designed to solve efficiently this last problem. A third problem devoted to maintenance scheduling in wind farm context is also studied in this work. First the problem is formulated as a deterministic linear bicriteria mixed integer program, then an epsilon constraint is developed to solve it. An extension to a maintenance planning problem involving a long horizon is also addressed using a simulation approach. This last part also considers maintenance strategies selection. Both developed approaches show the existing conflicts between energy production maximization and maintenance costs minimization
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Guo, Zigang. "Optimization of stochastic vehicle routing with soft time windows." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36758255.

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Chen, Yujie. "Optimisation for large-scale maintenance, scheduling and vehicle routing problems." Thesis, University of York, 2017. http://etheses.whiterose.ac.uk/16107/.

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Solving real-world combinatorial problems is involved in many industry fields to minimise operational cost or to maximise profit, or both. Along with continuous growth in computing power, many asset management decision-making processes that were originally solved by hand now tend to be based on big data analysis. Larger scale problem can be solved and more detailed operation instructions can be delivered. In this thesis, we investigate models and algorithms to solve large scale Geographically Distributed asset Maintenance Problems (GDMP). Our study of the problem was motivated by our business partner, Gaist solutions Ltd., to optimise scheduling of maintenance actions for a drainage system in an urban area. The models and solution methods proposed in the thesis can be applied to many similar issues arising in other industry fields. The thesis contains three parts. We firstly built a risk driven model considering vehicle routing problems and the asset degradation information. A hyperheuristic method embedded with customised low-level heuristics is employed to solve our real-world drainage maintenance problem in Blackpool. Computational results show that our hyperheuristic approach can, within reasonable CPU time, produce much higher quality solutions than the scheduling strategy currently implemented by Blackpool council. We then attempt to develop more efficient solution approaches to tackle our GDMP. We study various hyperheuristics and propose efficient local search strategies in part II. We present computational results on standard periodic vehicle routing problem instances and our GDMP instances. Based on manifold experimental evidences, we summarise the principles of designing heuristic based solution approaches to solve combinatorial problems. Last bu not least, we investigate a related decision making problem from highway maintenance, that is again of interest to Gaist solutions Ltd. We aim to make a strategical decision to choose a cost effective method of delivering the road inspection at a national scale. We build the analysis based on the Chinese Postman Problem and theoretically proof the modelling feasibility in real-world road inspection situations. We also propose a novel graph reduction process to allow effective computation over very large data sets.
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Bowden, Zachary E. "Behavioral Logistics and Fatigue Management in Vehicle Routing and Scheduling Problems." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/79792.

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The vehicle routing problem (VRP), is a classic optimization problem that aims to determine the optimal set of routes for a fleet of vehicles to meet the demands of a set of customers. The VRP has been studied for many decades and as such, there are many variants and extensions to the original problem. The research presented here focuses on two different types of vehicle routing and scheduling planning problems: car shipping and fatigue-aware scheduling. In addition to modeling and solving the car shipping problem, this research presents a novel way for ways in which drivers can describe their route preferences in a decision support system. This work also introduces the first fatigue-aware vehicle scheduling problem called the Truck Driver Scheduling Problem with Fatigue Management (TDSPFM). The TDSPFM is utilized to produce schedules that keep the drivers more alert than existing commercial vehicle regulations. Finally, this work analyzes the effect of the starting alertness level on driver alertness for the remainder of the work week and examines a critical shortcoming in existing regulations.
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Guo, Zigang, and 郭自剛. "Optimization of stochastic vehicle routing with soft time windows." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36758255.

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Books on the topic "Vehicle routing and scheduling"

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Eibl, Peter. Computerised vehicle routing and scheduling in road transport. Aldershot: Avebury, 1996.

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On method and system design for a problem in vehicle routing and scheduling. Lappeenranta: Lappeenranta University of Technology, 1987.

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Blackham, R. B. Application of logic and constraint programming techniques for vehicle routing and scheduling problems. Huddersfield: The Polytechnic of Huddersfield. School of Computing and Mathematics, 1990.

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Weber, Rolf. Vehicle Routing- und Scheduling-Probleme unter besonderer Berücksichtigung von Dial-a-Ride-Problemen. München: V. Florentz, 1985.

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Toth, Paolo, and Daniele Vigo, eds. Vehicle Routing. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2014. http://dx.doi.org/10.1137/1.9781611973594.

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Thorpe, J. C. Vehicle scheduling. Manchester: UMIST, 1992.

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Caric, Tonci, and Hrvoje Gold. Vehicle routing problem. Rijek, Crotia: InTech, 2008.

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Labadie, Nacima, Christian Prins, and Caroline Prodhon. Metaheuristics for Vehicle Routing Problems. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119136767.

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Ferrucci, Francesco. Pro-active Dynamic Vehicle Routing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33472-6.

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Ronen, David. Perspective on practical aspects of truck routing and scheduling. Monterey, Calif: Naval Postgraduate School, 1987.

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Book chapters on the topic "Vehicle routing and scheduling"

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Christiansen, Marielle, and Kjetil Fagerholt. "Chapter 13: Ship Routing and Scheduling in Industrial and Tramp Shipping." In Vehicle Routing, 381–408. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2014. http://dx.doi.org/10.1137/1.9781611973594.ch13.

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Goetschalckx, Marc. "Vehicle Routing and Scheduling." In Supply Chain Engineering, 271–430. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-6512-7_9.

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Lahyani, Rahma, Frédéric Semet, and Benoît Trouillet. "Vehicle Routing Problems with Scheduling Constraints." In Metaheuristics for Production Scheduling, 433–63. Hoboken, NJ USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118731598.ch16.

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Ullrich, Christian Alexander. "Supply Chain Scheduling: Integrated machine scheduling and vehicle routing." In Issues in Supply Chain Scheduling and Contracting, 17–52. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-03769-7_3.

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Desrosiers, J., F. Soumis, M. Desrochers, and M. Sauvé. "Vehicle routing and scheduling with time windows." In Mathematical Programming Studies, 249–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/bfb0121107.

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Ball, Michael O. "Vehicle Routing and Scheduling: Theory and Practice." In Operations Research Proceedings, 174. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74862-2_45.

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Stumpf, Petra. "Vehicle Routing and Scheduling for Trunk Haulage." In Advances in Distribution Logistics, 341–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-46865-0_15.

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Lam, Edward, Pascal Van Hentenryck, and Philip Kilby. "Joint Vehicle and Crew Routing and Scheduling." In Lecture Notes in Computer Science, 654–70. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23219-5_45.

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Hsu, Tienté, Gilles Gonçalves, and Rémy Dupas. "Metaheuristics for the Solution of Vehicle Routing Problems in a Dynamic Context." In Metaheuristics for Production Scheduling, 373–400. Hoboken, NJ USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118731598.ch14.

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Meyer, Christoph Manuel. "Dispatchers' Tasks in Combined Vehicle Routing and Break Scheduling." In Vehicle Routing under Consideration of Driving and Working Hours, 25–38. Wiesbaden: Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6732-9_3.

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Conference papers on the topic "Vehicle routing and scheduling"

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Supithak, Anchalee, Wisut Supithak, and Phusanisa Tosak. "Vehicle Scheduling for Tourism Routing Problem." In 2021 6th International Conference on Business and Industrial Research (ICBIR). IEEE, 2021. http://dx.doi.org/10.1109/icbir52339.2021.9465844.

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Rodney, Demane, Alan Soper, and Chris Walshaw. "The application of Multilevel Refinement to the Vehicle Routing Problem." In 2007 IEEE Symposium on Computational Intelligence in Scheduling. IEEE, 2007. http://dx.doi.org/10.1109/scis.2007.367692.

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Chang, Tsung-Sheng, and Sian-Da Wang. "Multi-trip vehicle routing and scheduling problems." In Industrial Engineering (CIE-40). IEEE, 2010. http://dx.doi.org/10.1109/iccie.2010.5668326.

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Shahparvari, Sh, B. Abbasi, P. Chhetri, and A. Abareshi. "Vehicle routing and scheduling for bushfire emergency evacuation." In 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2015. http://dx.doi.org/10.1109/ieem.2015.7385737.

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Goel, A., and V. Gruhn. "Drivers' working hours in vehicle routing and scheduling." In 2006 IEEE Intelligent Transportation Systems Conference. IEEE, 2006. http://dx.doi.org/10.1109/itsc.2006.1707399.

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Ursani, Ziauddin, Ruhul Sarker, and Hussein A. Abbass. "Improving the Performance of Genetic Algorithm in Capacitated Vehicle Routing Problem using Self Imposed Constraints." In 2007 IEEE Symposium on Computational Intelligence in Scheduling. IEEE, 2007. http://dx.doi.org/10.1109/scis.2007.367693.

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Jiang, Weigang, Yuanbiao Zhang, and Jianwen Xie. "A particle swarm optimization algorithm with crossover for vehicle routing problem with time windows." In 2009 IEEE Symposium on Computational Intelligence in Scheduling (CI-Sched). IEEE, 2009. http://dx.doi.org/10.1109/scis.2009.4927022.

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Pascaru, Cosmin, and Paul Diac. "Vehicle Routing and Scheduling for Regular Mobile Healthcare Services." In 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2018. http://dx.doi.org/10.1109/ictai.2018.00080.

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Weinstein, Amanda, and Corey Schumacher. "UAV Scheduling via the Vehicle Routing Problem with Time Windows." In AIAA Infotech@Aerospace 2007 Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2007. http://dx.doi.org/10.2514/6.2007-2839.

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Yin, Peng-Yeng, Ya-Lan Chuang, Sin-Ru Lyu, and Ching-Ying Chen. "Collaborative Vehicle Routing and Scheduling with Cross-Docks under Uncertainty." In 2015 IEEE Conference on Collaboration and Internet Computing (CIC). IEEE, 2015. http://dx.doi.org/10.1109/cic.2015.19.

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Reports on the topic "Vehicle routing and scheduling"

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NETROLOGIC INC DAYTON OH. Microcomputer-Based Vehicle Routing and Scheduling. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada238755.

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Klein, A. J. Microcomputer-based vehicle routing and scheduling: An overview. Office of Scientific and Technical Information (OSTI), August 1987. http://dx.doi.org/10.2172/6203643.

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Whitley, L. D., and Adele E. Howe. Exploiting Elementary Landscapes for TSP, Vehicle Routing and Scheduling. Fort Belvoir, VA: Defense Technical Information Center, September 2015. http://dx.doi.org/10.21236/ada622665.

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Rodin, Ervin Y. Air Transportation Network Routing and Scheduling. Fort Belvoir, VA: Defense Technical Information Center, February 2002. http://dx.doi.org/10.21236/ada419004.

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Rodin, Ervin Y. Air Transportation Network Routing and Scheduling. Fort Belvoir, VA: Defense Technical Information Center, February 2002. http://dx.doi.org/10.21236/ada419632.

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Hall, William G., Howard K. Hung, and Robert E. Chapman. Paratransit advanced routing and scheduling system documentation :. Gaithersburg, MD: National Bureau of Standards, 1985. http://dx.doi.org/10.6028/nbs.ir.85-3174.

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Hung, Howard K., William G. Hall, and Robert E. Chapman. Paratransit advanced routing and scheduling system documentation :. Gaithersburg, MD: National Bureau of Standards, 1985. http://dx.doi.org/10.6028/nbs.ir.85-3178.

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COLUMBIA UNIV NEW YORK. Analytical Analysis of Vehicle Routing and Inventory Routing Problems. Fort Belvoir, VA: Defense Technical Information Center, December 1998. http://dx.doi.org/10.21236/ada358629.

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Rodin, Ervin Y., and Allen McCoy. Simulation and Optimization Methodologies and Military Transportation Network Routing and Scheduling. Fort Belvoir, VA: Defense Technical Information Center, August 2008. http://dx.doi.org/10.21236/ada499000.

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Rodin, Ervin Y. Graduate and Undergraduate Studies in Optimizing Air Transport Scheduling and Routing. Fort Belvoir, VA: Defense Technical Information Center, April 2000. http://dx.doi.org/10.21236/ada389279.

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