Relevant bibliographies by topics / Rich Vehicle Routing Problems

Contents

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

Academic literature on the topic 'Rich Vehicle Routing Problems'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Rich Vehicle Routing Problems"

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Hartl, Richard F., Geir Hasle, and Gerrit K. Janssens. "Special issue on Rich Vehicle Routing Problems." Central European Journal of Operations Research 14, no. 2 (June 2006): 103–4. http://dx.doi.org/10.1007/s10100-006-0162-9.

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Lahyani, Rahma. "Unified matheuristic for solving rich vehicle routing problems." 4OR 13, no. 2 (December 11, 2014): 223–24. http://dx.doi.org/10.1007/s10288-014-0278-z.

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Lacomme, Philippe, Gwénaël Rault, and Marc Sevaux. "Integrated decision support system for rich vehicle routing problems." Expert Systems with Applications 178 (September 2021): 114998. http://dx.doi.org/10.1016/j.eswa.2021.114998.

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Lahyani, Rahma, Mahdi Khemakhem, and Frédéric Semet. "Rich vehicle routing problems: From a taxonomy to a definition." European Journal of Operational Research 241, no. 1 (February 2015): 1–14. http://dx.doi.org/10.1016/j.ejor.2014.07.048.

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Qi, Mingyao, Cheng Peng, and Xiaoyu Huang. "General Metaheuristic Algorithm for a Set of Rich Vehicle Routing Problems." Transportation Research Record: Journal of the Transportation Research Board 2548, no. 1 (January 2016): 97–106. http://dx.doi.org/10.3141/2548-12.

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Nalepa, Jakub, and Miroslaw Blocho. "Adaptive cooperation in parallel memetic algorithms for rich vehicle routing problems." International Journal of Grid and Utility Computing 9, no. 2 (2018): 179. http://dx.doi.org/10.1504/ijguc.2018.091724.

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Nalepa, Jakub, and Miroslaw Blocho. "Adaptive cooperation in parallel memetic algorithms for rich vehicle routing problems." International Journal of Grid and Utility Computing 9, no. 2 (2018): 179. http://dx.doi.org/10.1504/ijguc.2018.10012798.

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Setiawan, Fran, Nur Aini Masruroh, and Zita Iga Pramuditha. "On Modelling and Solving Heterogeneous Vehicle Routing Problem with Multi-Trips and Multi-Products." Jurnal Teknik Industri 21, no. 2 (December 16, 2019): 91–104. http://dx.doi.org/10.9744/jti.21.2.91-104.

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Vehicle routing problem (VRP) is a model to determine an optimal routing plan for a fleet of homogeneous vehicles to serve a set customer which some operational constraints are satisfied. In most practical distribution problems, customer demands are served using heterogeneous fleet of vehicles. This kind of VRP is called Heterogeneous Vehicle Routing Problem (HVRP). HVRP has evolved into a rich research area because of its practical. There were many studies of rich extensions of the standar HVRP. This research aims to enrich the extentions of HVRP which is motivated by real case in one of pharmacy distribution company in Indonesia which is delivered multi-products to its 55 customers by allowing some vehicles which has small capacity to perform multi-trips. This problem is called Heterogeneous Vehicle Routing Problem with Multi-Trips and Multi-Products (HVRPMTMP).The mixed integer linear programming is developed based on four-index vehicle flow formulation. The model can be used generally in the same context of distribution problem. HVRPMTMP is generally NP-Hard problem, so the computational time using branch and bound in LINGO 16.0 is increasing exponentially by increasing the number of customers. Genetic algorithm is proposed to solve the real case. The result of the proposed GA can reduce the total cost from Rp 352540.6,- to Rp 180555,- or 48.78% from the current company policy.
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Derigs, Ulrich, and Ulrich Vogel. "Experience with a framework for developing heuristics for solving rich vehicle routing problems." Journal of Heuristics 20, no. 1 (August 17, 2013): 75–106. http://dx.doi.org/10.1007/s10732-013-9232-z.

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Derigs, Ulrich, and Markus Pullmann. "A computational study comparing different multiple neighbourhood strategies for solving rich vehicle routing problems." IMA Journal of Management Mathematics 27, no. 1 (December 5, 2013): 3–23. http://dx.doi.org/10.1093/imaman/dpt022.

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Dissertations / Theses on the topic "Rich Vehicle Routing Problems"

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Quintero, Araújo Carlos Leonardo. "Applications of simheuristics and horizontal cooperation concepts in rich vehicle routing problems." Doctoral thesis, Universitat Oberta de Catalunya, 2017. http://hdl.handle.net/10803/460831.

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En una economia globalitzada, les companyies s’enfronten a nombrosos reptes associats a les complexes tasques de logística i distribució. Gràcies al desenvolupament de les tecnologies de la informació i la comunicació, els clients es troben en qualsevol part del món, però també els competidors. Per tant, les companyies necessiten ser més competitives, cosa que implica eficiència econòmica i sostenibilitat. Una estratègia que les firmes poden seguir per a ser més competitives és la cooperació horitzontal, que genera economies d’escala, increment en la utilització de recursos i reducció de costos. Molts d’aquests reptes en logística i transport, així com algunes estratègies de cooperació horitzontal, es poden abordar mitjançant diferents variants del conegut problema d’encaminament de vehicles (VRP). Malgrat que el VRP ha estat àmpliament estudiat, la majoria dels treballs publicats corresponen a versions massa simplificades de la realitat. Per a omplir aquest buit entre la teoria i les aplicacions de la vida real, fa poc que ha sorgit el concepte de problemes «enriquits» d’encaminament de vehicles (RVRP). Per tant, es necessiten nous mètodes de solució per a resoldre eficientment nous RVRP, així com per a quantificar els beneficis generats per la implementació d’estratègies de cooperació horitzontal en aplicacions reals, de manera que es puguin fer servir com a suport per a la presa de decisions. Per a abordar aquesta varietat de problemes es proposen diferents metaheurístiques basades en aleatorització esbiaixada. Aquests mètodes es combinen amb simulació (fet que es coneix com simheurístiques) per a resoldre situacions en les quals apareix la incertesa. Els mètodes proposats han estat avaluats utilitzant instàncies de prova tant teòriques com de la vida real.
En una economía globalizada, las compañías se enfrentan a numerosos retos asociados a las complejas tareas de logística y distribución. Gracias al desarrollo de las tecnologías de la información y la comunicación, los clientes se encuentran en cualquier lugar del mundo, pero también los competidores. Por lo tanto, las compañías necesitan ser más competitivas, lo que implica eficiencia económica y sostenibilidad. Una estrategia que las firmas pueden seguir para ser más competitivas es la cooperación horizontal, generando así economías de escala, incremento en la utilización de recursos y reducción de costes. Muchos de estos retos en logística y transporte, así como algunas estrategias de cooperación horizontal, pueden abordarse mediante diferentes variantes del conocido problema de enrutamiento de vehículos (VRP). Pese a que el VRP ha sido ampliamente estudiado, la mayoría de los trabajos publicados corresponden a versiones simplificadas de la realidad. Para llenar este vacío entre la teoría y las aplicaciones de la vida real, recientemente ha surgido el concepto de problemas «enriquecidos» de enrutamiento de vehículos (RVRP). Por lo tanto, se necesitan nuevos métodos de solución para resolver de forma eficiente nuevos RVRP, así como para cuantificar los beneficios generados por la implementación de estrategias de cooperación horizontal en aplicaciones reales, de modo que puedan usarse como apoyo para la toma de decisiones. Para abordar tal variedad de problemas se proponen diferentes metaheurísticas basadas en aleatorización sesgada. Estos métodos se combinan con simulación (lo que se conoce como simheurísticas) para resolver situaciones en las que aparece la incertidumbre. Los métodos propuestos han sido evaluados utilizando instancias de prueba tanto teóricas como de la vida real.
In a globalized economy, companies have to face different challenges related to the complexity of logistics and distribution strategies. Due to the development of information and communication technologies (ICT), customers and competitors may be located anywhere in the world. Thus, companies need to be more competitive, which entails efficiency from both an economic and a sustainability point of view. One strategy that companies can follow to become more competitive is to cooperate with other firms, a strategy known as horizontal cooperation (HC), allowing the use of economies of scale, increased resource utilization levels, and reduced costs. Many of these logistics and transport challenges, as well as certain HC strategies, may be addressed using variants of the vehicle routing problem (VRP). Even though VRP has been widely studied, the majority of research published corresponds to oversimplified versions of the reality. To fill the existing gap between the academic literature and real-life applications, the concept of rich VRPs (RVRPs) has emerged in the past few years in order to provide a closer representation of real-life situations. Accordingly, new approaches are required to solve new RVRPs efficiently and to quantify the benefits generated through the use of HC strategies in real applications. Thus, they can be used to support decision-making processes regarding different degrees of implementation of HC. Several metaheuristic methods based on biased randomization techniques are proposed. Additionally, these methods are hybridized with simulation (ie simheuristics) to tackle the presence of uncertainty. The proposed approaches are tested using a large set of theoretical and real-life benchmarks.
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Vogel, Ulrich [Verfasser]. "A flexible metaheuristic framework for solving rich vehicle routing problems / Ulrich Vogel." Aachen : Shaker, 2012. http://d-nb.info/1069048984/34.

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Cáceres, Cruz José de Jesús. "Randomized Algorithms for Rich Vehicle Routing Problems: From a Specialized Approach to a Generic Methodology." Doctoral thesis, Universitat Oberta de Catalunya, 2013. http://hdl.handle.net/10803/127153.

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El Problema de Enrutamiento de Vehículos (VRP) y sus diferentes variantes básicas son un dominio ampliamente estudiado en la comunidad científica de optimización. Algunos estudios han utilizado combinaciones específicas de restricciones encontradas en la vida real para definir los emergentes VRP Enriquecidos. Este trabajo aborda la integración de heurísticas, probabilidad sesgada, simulación, técnicas de computación distribuida & paralelas, y programación con restricciones. Los enfoques propuestos han solucionado algunas variantes del VRP: en primer lugar, las familias deterministas: VRP con flotas Heterogéneas (HVRP), VRP con flotas Heterogéneas y costo variable (HVRP-V), VRP con flota Heterogénea y Múltiples viajes (HVRPM), VRP con matriz de costo Asimétrica (AVRP), VRP con flota Heterogénea y matriz de costo Asimétrica (HAVRP), VRP con ventanas de Tiempo (VRPTW), y VRP Distancia limitada (DCVRP); en segundo lugar, las familias de naturaleza estocástica: VRP con Demandas estocásticas (VRPSD), y Problemas de Inventario y Enrutamiento de Vehículos con Demandas estocásticas (IRPSD). Una extensa revisión bibliográfica se ha realizado para cada una de estas variantes. Un primer enfoque propone la combinación de una aleatorización sesgada con heurísticas clásicas para la solución de problemas deterministas. Un segundo enfoque se centra en la combinación de heurísticas aleatorias con simulación (Simheuristics) para ser aplicados sobre los problemas estocásticos comentados. Por último, se propone un tercer enfoque basado en el trabajo conjunto de heurísticas aleatorias con programación de restricciones para resolver varios tipos de problemas de enrutamiento. Los algoritmos heurísticos desarrollados han sido aplicados en varios casos de referencia --entre ellos, dos estudios de casos reales de distribución en España-- y los resultados obtenidos son, en general, prometedores y útiles para los decisores.
The Vehicle Routing Problem (VRP) is a well known domain in optimization research community. Its different basic variants have been widely explored in the literature. Some studies have considered specific combinations of real-life constraints to define the emerging Rich VRP scopes. This work deals with the integration of heuristics, biased probability, simulation, parallel & distributed computing techniques, and constraint programming. The proposed approaches are tested for solving some variants of VRPs, namely, first, the deterministic families: Heterogeneous VRP (HVRP), Heterogeneous VRP with Variable cost (HVRP-V), Heterogeneous fleet VRP with Multi-trips (HVRPM), Asymmetric cost matrix VRP (AVRP), Heterogeneous fleet with Asymmetric cost matrix VRP (HAVRP), VRP with Time Windows (VRPTW), and Distance-Constrained VRP (DCVRP); second, the stochastic nature families: VRP with Stochastic Demands (VRPSD), and Inventory Routing Problem with Stochastic Demands (IRPSD). An extensive literature review is performed for all these variants, focusing on the main contributions of each work. A first approach proposes a biased-randomization of classical heuristics for solving the deterministic problems addressed here. A second approach is centered on the combination of randomized heuristics with simulation (Simheuristics) to be applied on the commented stochastic problems. Finally, a third approach based on the joined work of randomized heuristics with constraint programming is proposed to solve several types of routing problems. The developed heuristic algorithms are tested in several benchmark instances --between these, two real-life case studies in Spain are considered-- and the results obtained are, on average, highly promising and useful for decision makers.
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Seixas, Michel Povlovitsch. "Heuristic and exact methods applied to a rich vehicle routing and scheduling problem." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/3/3135/tde-09072014-111258/.

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This study considers a vehicle routing problem with time windows, accessibility restrictions on customers and a fleet that is heterogeneous with regard to capacity, average speed and cost. A vehicle can perform multiple routes per day, all starting and ending at a single depot, and it is assigned to a single driver, whose total work hours are limited. The available fleet is divided into an owned fleet, for which a variable cost is incurred, and a chartered fleet, for which only a fixed cost is incurred for each vehicle used. A column generation algorithm embedded in a branch-and-bound framework is proposed. The column generation pricing subproblem required a specific elementary shortest path problem with resource constraints algorithm to address the possibility for each vehicle performing multiple routes per day and to address the need to determine the workdays start time within the planning horizon. To make the algorithm efficient, a constructive heuristic and a learning metaheuristic algorithm based on tabu search were also developed. Both were used on branch-and-bound tree nodes to generate a good initial solution to the linear restricted master problem; particularly, to find a good initial primal bound to the branch-and-bound tree.
Este estudo aborda um problema de roteirização de veículos com janelas de tempo, restrições de acessibilidade nos clientes e uma frota que é heterogênea em relação à capacidade de carga, velocidade média de deslocamento e custo. Um veículo pode percorrer múltiplas rotas por dia, todas começando e terminando em um mesmo depósito, e está designado a um único motorista, cujo total de horas trabalhadas no dia está limitado a um valor máximo. A frota disponível é dividida em uma frota própria, para a qual um custo variável é incorrido, e uma frota de freteiros, para a qual apenas um custo fixo é incorrido para cada veículo utilizado. Um algoritmo baseado em geração de colunas, integrado a um procedimento de branch-and-bound, é proposto neste estudo. O subproblema de precificação da geração de colunas requereu um algoritmo específico para o problema do caminho mínimo elementar com restrições sobre recursos capaz de lidar com a possibilidade de cada veículo percorrer múltiplas rotas por dia e capaz de lidar com a necessidade de determinar o instante de início do dia de trabalho do motorista dentro do horizonte de planejamento. Para tornar o algoritmo eficiente, uma heurística construtiva e uma heurística de melhoria baseada em busca tabu também foram desenvolvidos. Ambos são utilizados nos nós da árvore de branch-and-bound para gerar boas soluções iniciais para o problema mestre restrito da geração de colunas; particularmente, para encontrar um bom limitante primal inicial para a árvore de branch-and-bound.
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Vogel, Ulrich [Verfasser], Ulrich [Akademischer Betreuer] Derigs, and Dirk [Akademischer Betreuer] Briskorn. "A flexible metaheuristic framework for solving rich vehicle routing problems : Formulierung, Implementierung und Anwendung eines kognitionsbasierten Simulationsmodells / Ulrich Vogel. Gutachter: Ulrich Derigs ; Dirk Briskorn." Köln : Universitäts- und Stadtbibliothek Köln, 2011. http://d-nb.info/1038360595/34.

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Vogel, Ulrich [Verfasser], Ulrich Akademischer Betreuer] Derigs, and Dirk [Akademischer Betreuer] [Briskorn. "A flexible metaheuristic framework for solving rich vehicle routing problems : Formulierung, Implementierung und Anwendung eines kognitionsbasierten Simulationsmodells / Ulrich Vogel. Gutachter: Ulrich Derigs ; Dirk Briskorn." Köln : Universitäts- und Stadtbibliothek Köln, 2011. http://d-nb.info/1038360595/34.

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Pullmann, Markus Dirk [Verfasser]. "Untersuchungen zu Rich Vehicle Routing Problemen im Supply Chain Management : Neue algorithmische Strategien und spezifische Problemstellungen / Markus Dirk Pullmann." Aachen : Shaker, 2014. http://d-nb.info/1058315439/34.

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Pullmann, Markus [Verfasser]. "Untersuchungen zu Rich Vehicle Routing Problemen im Supply Chain Management : Neue algorithmische Strategien und spezifische Problemstellungen / Markus Dirk Pullmann." Aachen : Shaker, 2014. http://nbn-resolving.de/urn:nbn:de:101:1-201409147581.

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Lahyani, Rahma. "Une matheuristique unifiée pour résoudre des problèmes de tournées de véhicules riches." Thesis, Ecole centrale de Lille, 2014. http://www.theses.fr/2014ECLI0011/document.

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L’objectif de cette thèse est de développer un cadre méthodologique pour les problèmes de tournées de véhicules riches (RVRPs). Nous présentons d’abord une taxonomie et une définition élaborée des RVRPs basée sur une analyse typologique réalisée en fonction de deux critères discriminatoires. Dans cette thèse, nous nous intéressons à la résolution du problème de tournées de véhicules multi-dépôt multi-compartiment multi-produits avec fenêtres de temps (MDMCMCm-VRPTW). Nous proposons une heuristique de génération de colonnes unifiée qui inclut une matheuristique de type VNS. La matheuristique combine plusieurs heuristiques de routage de type destruction et insertion ainsi que des procédures efficaces de contrôle de réalisabilité des contraintes afin de résoudre le MDMCMCm-VRPTW pour un seul véhicule. Deux voisinages de chargement, basés sur la résolution de programmes mathématiques sont proposées. Des études expérimentales approfondies sont conduites sur un ensemble de 191 instances pour des VRPs moins complexes. Les expérimentations valident la compétitivité de la matheuristique unifiée. Une analyse de sensibilité révèle l’importance de certains choix algorithmiques et des voisinages de chargement pour parvenir à des solutions de très bonne qualité. La matheuristique basée sur la méthode de VNS est intégrée dans l’heuristique de génération de colonnes pour résoudre le MDMCMCm-VRPTW. Nous proposons une méthode exacte de post-traitement capable d’optimiser l’affectation des clients aux tournées de véhicules. Enfin, nous résolvons un RVRP qui survient dans le processus de collecte de l’huile d’olive en Tunisie à l’aide d’un algorithme exact de type branch-and-cut
The purpose of this thesis is to develop a solution framework for Rich Vehicle Routing Problems (RVRPs). We first provide a comprehensive survey of the RVRP literature as well as a taxonomy. Selected papers addressing various variants are classified according to the proposed taxonomy. A cluster analysis based on two discriminating criteria is performed and leads to define RVRPs. In this thesis we are interested in solving a multi-depot multi-compartment multi-commodity vehicle routing problem with time windows (MDMCMCm-VRPTW). We propose a unified column generation heuristic cooperating with a variable neighborhood search (VNS) matheuristic. The VNS combines several removal and insertion routing heuristics as well as computationally efficient constraint checking. Two loading neighborhoods based on the solution of mathematical programs are proposed to intensify the search. On a set of 191 instances of less complex routing problems, the unified matheuristic turns to be competitive. A sensitivity analysis, performed on more complex generated instances reveals the importance of some algorithmic features and of loading neighborhoods for reaching high quality solutions. The VNS based matheuristic is embedded in a column generation heuristic to solve the MDMCMCm-VRPTW. We propose an exact post-processing method to optimize the assignment ofcustomers to vehicle routes. Last, we introduce, model and solve to optimality a RVRP arising in the olive oil collection process in Tunisia. We propose an exact branch-and-cut algorithm to solve the problem. We evaluate the performance of the algorithm on real data sets under different transportation scenarios
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Zhang, Xinglong. "Network vehicle routing problems." Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/21710.

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Books on the topic "Rich Vehicle Routing Problems"

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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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Vehicle routing: Problems, methods, and applications. Philadelphia: Society for Industrial and Applied Mathematics, 2014.

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Derbel, Houda, Bassem Jarboui, and Patrick Siarry, eds. Green Transportation and New Advances in Vehicle Routing Problems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45312-1.

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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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Nurmaulidar. Optimasi distribusi pangan menggunakan model capacitated vehicle routing problems dan algoritma berevolusi untuk sistem informasi bencana: Laporan hasil penelitian strategis nasional. Banda Aceh]: Universitas Syiah Kuala, 2010.

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Prins, Christian, Caroline Prodhon, and Nacima Labadie. Metaheuristics for Vehicle Routing Problems. Wiley & Sons, Incorporated, John, 2016.

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Prins, Christian, Nacima LaBadie, and Caroline Prodhon. Metaheuristics for Vehicle Routing Problems. Wiley & Sons, Incorporated, John, 2016.

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Prins, Christian, Caroline Prodhon, and Nacima Labadie. Metaheuristics for Vehicle Routing Problems. Wiley & Sons, Incorporated, John, 2016.

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Vansteenwegen, Pieter, and Aldy Gunawan. Orienteering Problems: Models and Algorithms for Vehicle Routing Problems with Profits. Springer, 2019.

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Siarry, Patrick, Houda Derbel, and Bassem Jarboui. Green Transportation and New Advances in Vehicle Routing Problems. Springer, 2020.

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Book chapters on the topic "Rich Vehicle Routing Problems"

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Doerner, Karl F., and Verena Schmid. "Survey: Matheuristics for Rich Vehicle Routing Problems." In Hybrid Metaheuristics, 206–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16054-7_15.

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Zunic, Emir, Sead Delalic, Dzenana Donko, and Haris Supic. "A Cluster-Based Approach to Solve Rich Vehicle Routing Problems." In Lecture Notes in Business Information Processing, 103–23. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71846-6_6.

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Reinholz, Andreas, and Holger Schneider. "Ein prozess- und objektorientiertes Modellierungskonzept für praxisnahe Rich Vehicle Routing Problems." In Große Netze der Logistik, 153–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-71048-6_7.

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Sim, Kevin, Emma Hart, Neil Urquhart, and Tim Pigden. "A New Rich Vehicle Routing Problem Model and Benchmark Resource." In Computational Methods in Applied Sciences, 503–18. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89988-6_30.

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Mancini, Simona. "A New Large Neighborhood Search Based Matheuristic Framework for Rich Vehicle Routing Problems." In Computer Aided Systems Theory – EUROCAST 2015, 789–96. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27340-2_97.

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Bartodziej, Paul, Ulrich Derigs, and Ulrich Vogel. "On the Potentials of Parallelizing Large Neighbourhood Search for Rich Vehicle Routing Problems." In Lecture Notes in Computer Science, 216–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13800-3_22.

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van Benthem, Tim, Mark Bergman, and Martijn Mes. "Solving a Bi-Objective Rich Vehicle Routing Problem with Customer Prioritization." In Lecture Notes in Computer Science, 183–99. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59747-4_12.

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Pellegrini, Paola, Daniela Favaretto, and Elena Moretti. "Multiple Ant Colony Optimization for a Rich Vehicle Routing Problem: A Case Study." In Lecture Notes in Computer Science, 627–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74827-4_79.

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Derigs, Ulrich, and Thomas Döhmer. "Router: A Fast and Flexible Local Search Algorithm for a Class of Rich Vehicle Routing Problems." In Operations Research Proceedings 2004, 144–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/3-540-27679-3_18.

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Žunić, Emir, Sead Delalić, Dženana Đonko, and Haris Šupić. "Two-Phase Approach for Solving the Rich Vehicle Routing Problem Based on Firefly Algorithm Clustering." In Proceedings of Sixth International Congress on Information and Communication Technology, 253–62. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2377-6_25.

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Conference papers on the topic "Rich Vehicle Routing Problems"

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Agany Manyiel, Joseph Mabor, Yew Kwang Hooi, and Mohamed Nordin b. Zakaria. "Multi-Population Genetic Algorithm for Rich Vehicle Routing Problems." In 2021 International Conference on Computer & Information Sciences (ICCOINS). IEEE, 2021. http://dx.doi.org/10.1109/iccoins49721.2021.9497136.

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Mayer, Thomas, Tobias Uhlig, and Oliver Rose. "An open-source discrete event simulator for rich vehicle routing problems." In 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2016. http://dx.doi.org/10.1109/itsc.2016.7795725.

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Lahyani, Rahma, Mahdi Khemakhem, Habib Chabchoub, and Frederic Semet. "Design factors analysis for instances of rich vehicle routing problem." In 2011 4th International Conference on Logistics (LOGISTIQUA). IEEE, 2011. http://dx.doi.org/10.1109/logistiqua.2011.5939428.

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Masmoudi, Mariem, Mounir Benaissa, and Habib Chabchoub. "Mathematical modeling for a rich vehicle routing problem in E-commerce logistics distribution." In 2013 International Conference on Advanced Logistics and Transport (ICALT). IEEE, 2013. http://dx.doi.org/10.1109/icadlt.2013.6568474.

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Alemany, Gabriel, Jesica de Armas, Angel A. Juan, Alvaro Garcia-Sanchez, Roberto Garcia-Meizoso, and Miguel Ortega-Mier. "Combining Monte Carlo simulation with heuristics to solve a rich and real-life multi-depot vehicle routing problem." In 2016 Winter Simulation Conference (WSC). IEEE, 2016. http://dx.doi.org/10.1109/wsc.2016.7822285.

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Vidal, Thibaut. "Heuristics for vehicle routing problems." In SoICT 2017: The Eighth International Symposium on Information and Communication Technology. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3155133.3155139.

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Chen, Ruey-Maw, and Jia-Ci Guo. "Optimal Routing for Split Delivery Vehicle Routing Problems." In 2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2018. http://dx.doi.org/10.1109/iiai-aai.2018.00140.

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Hoffmann, Benjamin, Michael Guckert, Kevin Chalmers, and Neil Urquhart. "Simulating Dynamic Vehicle Routing Problems With Athos." In 33rd International ECMS Conference on Modelling and Simulation. ECMS, 2019. http://dx.doi.org/10.7148/2019-0296.

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Thangiah, Sam R., Olena Shmygelska, and William Mennell. "An agent architecture for vehicle routing problems." In the 2001 ACM symposium. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/372202.372445.

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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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Reports on the topic "Rich Vehicle Routing Problems"

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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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Figliozzi, Miguel. Freight Distribution Problems in Congested Urban Areas: Fast and Effective Solution Procedures to Time-Dependent Vehicle Routing Problems. Portland State University Library, January 2011. http://dx.doi.org/10.15760/trec.108.

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