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Auswahl der wissenschaftlichen Literatur zum Thema „Travelling salesman problem with time windows“
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Zeitschriftenartikel zum Thema "Travelling salesman problem with time windows"
Obi, Chris Jojo. „Using genetic algorithm to solve multiple traveling salesman problem and considering Carbon emissions“. Indian Journal of Science and Technology 13, Nr. 36 (26.09.2020): 3707–15. http://dx.doi.org/10.17485/ijst/v13i36.1316.
Der volle Inhalt der QuelleLópez-Ibáñez, Manuel, und Christian Blum. „Beam-ACO for the travelling salesman problem with time windows“. Computers & Operations Research 37, Nr. 9 (September 2010): 1570–83. http://dx.doi.org/10.1016/j.cor.2009.11.015.
Der volle Inhalt der QuelleMladenovic, Nenad, Raca Todosijevic und Dragan Urosevic. „An efficient General Variable Neighborhood Search for large Travelling Salesman Problem with Time Windows“. Yugoslav Journal of Operations Research 23, Nr. 1 (2013): 19–30. http://dx.doi.org/10.2298/yjor120530015m.
Der volle Inhalt der QuelleTae, Hyun-Chul, und Byung-In Kim. „Dynamic Programming Approach for Prize Colleting Travelling Salesman Problem with Time Windows“. IE interfaces 24, Nr. 2 (01.06.2011): 112–18. http://dx.doi.org/10.7232/ieif.2011.24.2.112.
Der volle Inhalt der QuelleAscheuer, Norbert, Matteo Fischetti und Martin Grötschel. „Solving the Asymmetric Travelling Salesman Problem with time windows by branch-and-cut“. Mathematical Programming 90, Nr. 3 (Mai 2001): 475–506. http://dx.doi.org/10.1007/pl00011432.
Der volle Inhalt der QuelleLópez-Ibáñez, Manuel, Christian Blum, Jeffrey W. Ohlmann und Barrett W. Thomas. „The travelling salesman problem with time windows: Adapting algorithms from travel-time to makespan optimization“. Applied Soft Computing 13, Nr. 9 (September 2013): 3806–15. http://dx.doi.org/10.1016/j.asoc.2013.05.009.
Der volle Inhalt der QuelleCheng, Chi-Bin, und Chun-Pin Mao. „A modified ant colony system for solving the travelling salesman problem with time windows“. Mathematical and Computer Modelling 46, Nr. 9-10 (November 2007): 1225–35. http://dx.doi.org/10.1016/j.mcm.2006.11.035.
Der volle Inhalt der QuelleHill, Stephen E., und Marco Lam. „A teaching exercise for the travelling salesman problem with time windows using real-world data“. International Journal of Information and Operations Management Education 5, Nr. 4 (2014): 363. http://dx.doi.org/10.1504/ijiome.2014.067566.
Der volle Inhalt der QuelleBudak, Gerçek, und Xin Chen. „Evaluation of the size of time windows for the travelling salesman problem in delivery operations“. Complex & Intelligent Systems 6, Nr. 3 (20.06.2020): 681–95. http://dx.doi.org/10.1007/s40747-020-00167-y.
Der volle Inhalt der QuelleBaltz, Andreas, Mourad El Ouali, Gerold Jäger, Volkmar Sauerland und Anand Srivastav. „Exact and heuristic algorithms for the Travelling Salesman Problem with Multiple Time Windows and Hotel Selection“. Journal of the Operational Research Society 66, Nr. 4 (April 2015): 615–26. http://dx.doi.org/10.1057/jors.2014.17.
Der volle Inhalt der QuelleDissertationen zum Thema "Travelling salesman problem with time windows"
Pavlovič, Dávid. „Problém obchodního cestujícího s časovými okny“. Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-442819.
Der volle Inhalt der QuelleRužička, Vladimír. „Aplikace problému Obchodního cestujícího v reálném prostředí distribuční společnosti“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236578.
Der volle Inhalt der QuelleAsan, N. Evren. „Offline And Online Disk Scheduling Problems“. Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607909/index.pdf.
Der volle Inhalt der QuellePtáčková, Michaela. „Optimalizace tras při rozvozu zásilek“. Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-264544.
Der volle Inhalt der QuelleYuan, Yuan. „Modèles et Algorithmes pour les Problèmes de Livraison du Dernier Kilomètre avec Plusieurs Options d'Expédition“. Thesis, Ecole centrale de Lille, 2019. http://www.theses.fr/2019ECLI0011.
Der volle Inhalt der QuelleIn this thesis, we study routing problems that arise in the context of last mile delivery when multiple delivery options are proposed to the customers. The most common option to deliver packages is home/workplace delivery. Besides, the delivery can be made to pick-up points such as dedicated lockers or stores. In recent years, a new concept called trunk/in-car delivery has been proposed. Here, customers' packages can be delivered to the trunks of cars. Our goal is to model and develop efficient solution approaches for routing problems in this context, in which each customer can have multiple shipping locations. First, we survey non-Hamiltonian routing problems. Then, we study the single-vehicle case in the considered context, which is modeled as a Generalized Traveling Salesman Problem with Time Windows (GTSPTW). Four mixed integer linear programming formulations and an efficient branch-and-cut algorithm are proposed. Finally, we study the multi-vehicle case which is denoted Generalized Vehicle Routing Problem with Time Windows (GVRPTW). An efficient column generation based heuristic is proposed to solve it
Mao, Chun-Pin, und 毛俊彬. „Applying Ant Colony Optimization in Solving the Traveling Salesman Problem with Time Windows“. Thesis, 2006. http://ndltd.ncl.edu.tw/handle/755779.
Der volle Inhalt der Quelle朝陽科技大學
工業工程與管理系碩士班
94
The traveling salesman problem with time windows (TSPTW) is a problem of finding a minimum cost tour where all cities must be visited exactly once within their requesting time windows. This problem has important applications in practice such as scheduling and routing problems. Savelsberg (1985) showed that simply finding a feasible solution of TSPTW is NP-complete. Traditional optimization algorithms generally need exponential computation time in solving such a problem. Thus, the development of approximate algorithms has received more and more attention in recent years. Ant colony optimization (ACO) is one of the most recent methods inspired by biological behavior for developing approximate algorithms. It has been shown to be efficient to solve traveling salesman problems. In this research, a modified meta-heuristic based on ACO is applied to solve the TSPTW. Testing results on benchmark instances demonstrate that the proposed approach performs well on problem instances with narrower time windows; in particular, optimum solutions are found for some small-scale problems.
Silva, João Carlos Lopes da. „Planeamento de rotas de distribuição“. Master's thesis, 2016. http://hdl.handle.net/10451/24881.
Der volle Inhalt der QuelleConsiderando um conjunto de clientes que necessitam de ser visitados num intervalo de tempo previamente conhecido, o Traveling Salesman Problem with Time Windows (TSPTW) consiste em determinar uma rota de custo mínimo, com início e fim num depósito, garantindo que todos os clientes sejam visitados na respetiva janela temporal. São conhecidos os clientes a servir, os custos e tempos de deslocação entre cada par de clientes e entre cada cliente e o depósito, os tempos de serviço e a janela temporal de cada cliente, bem como o tempo e distância máxima da rota. A rota tem associado um custo resultante da soma dos custos de deslocação. Existem diversas variantes do problema, pelo que nesta dissertação são estudadas as variantes do TSPTW com vista à minimização da distância total percorrida com tempos de espera, minimização da duração da rota com e sem possibilidade de tempos de espera, no caso de o veículo chegar ao cliente antes do início da respetiva janela temporal. Para cada problema, é considerado uma variação da amplitude das janelas temporais de cada cliente a ser visitado. O TSPTW pertence à classe de problemas NP-difícil, por ser uma extensão do clássico TSP. Na presente dissertação são propostos dois modelos para o TSPTW: um modelo baseado nas restrições de Miller-Tucker-Zemlin (MTZ) e um outro Modelo de Fluxo Agregado (MFA). Pretende-se comparar os modelos propostos na resolução de problemas para as diversas variantes em estudo, bem como a comparação da qualidade da correspondente relaxação linear. Para comparar os modelos propostos, foram utilizadas instâncias de referência da literatura. Com um número de clientes a variar entre 20 a 200 e com diferentes amplitudes de janelas temporais para cada problema, os métodos utilizados permitiram resolver os problemas, em que não era conhecido o seu valor ótimo.
Given a set of customers who need to be visited in a previously known time window, the Traveling Salesman Problem with Time Windows (TSPTW) is to determine a minimum cost route, starting and ending in a depot, ensuring that all customers are visited in the them time window. All customers to serve are known, cost and travel times between each pair of customers and between each customer and the depot, service times and the time window of each client, as well as the maximum time and route distance. The route has an associated cost, resulting from the sum of the travel costs. There are several variants of the problem, so this thesis is to studied TSPTW variants with goal to minimizing the total distance traveled with waiting times, minimizing the duration of the route with and without possibility of waiting times, in case of the vehicle reach the client before the start of respective time window. For each problem, it is considered a variation of the length of time windows of each client to be visited. The TSPTW belongs to the class of NP-hard problems, being an extension of the classic TSP. In this thesis two models are proposed for TSPTW: a model based on the constraints of Miller-Tucker-Zemlin (MTZ) and another Aggregated Flow Model (MFA). Aims to compare the formulations in getting the solutions of the several variants in study, as well as the quality of linear relaxation. To compare the models, it were used the literature reference instances. With a number of customers range from 20 to 200 with different ranges and time windows for each problem, the methods allow solving problems, that it was not known the optimal solution.
Amghar, Khalid. „Une heuristique de recherche à voisinage variable pour le problème du voyageur de commerce avec fenêtres de temps“. Thèse, 2016. http://hdl.handle.net/1866/16156.
Der volle Inhalt der QuelleWe adapt a general variable neighborhood search heuristic to solve the traveling salesman problem with time windows (TSPTW) where the objective is to minimize the completion time. We use efficient methods to check the feasibility and the profitability of a movement. We use a specific order to reduce the search space while exploring the neighborhoods. The resulting method is competitive with the state-of-the-art. We improve the best known solutions for two classes of instances and provide the results of multiple instances of TSPTW for the first time.
Buchteile zum Thema "Travelling salesman problem with time windows"
Qin, Hu, Andrew Lim und Dongsheng Xu. „The Selective Traveling Salesman Problem with Regular Working Time Windows“. In Studies in Computational Intelligence, 291–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92814-0_45.
Der volle Inhalt der QuelleBoland, Natashia, Mike Hewitt, Duc Minh Vu und Martin Savelsbergh. „Solving the Traveling Salesman Problem with Time Windows Through Dynamically Generated Time-Expanded Networks“. In Integration of AI and OR Techniques in Constraint Programming, 254–62. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59776-8_21.
Der volle Inhalt der QuelleBar-Yehuda, Reuven, Guy Even und Shimon Shahar. „On Approximating a Geometric Prize-Collecting Traveling Salesman Problem with Time Windows“. In Algorithms - ESA 2003, 55–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39658-1_8.
Der volle Inhalt der QuelleStützle, Thomas, und Holger H. Hoos. „Analysing the Run-Time Behaviour of Iterated Local Search for the Travelling Salesman Problem“. In Operations Research/Computer Science Interfaces Series, 589–611. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1507-4_26.
Der volle Inhalt der QuelleTüű-Szabó, Boldizsár, Péter Földesi und László T. Kóczy. „An Efficient New Memetic Method for the Traveling Salesman Problem with Time Windows“. In Lecture Notes in Computer Science, 426–36. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69456-6_35.
Der volle Inhalt der QuelleZhang, Yanyan, und Lixin Tang. „Solving Prize-Collecting Traveling Salesman Problem with Time Windows by Chaotic Neural Network“. In Advances in Neural Networks – ISNN 2007, 63–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72393-6_9.
Der volle Inhalt der QuelleRimmel, Arpad, Fabien Teytaud und Tristan Cazenave. „Optimization of the Nested Monte-Carlo Algorithm on the Traveling Salesman Problem with Time Windows“. In Applications of Evolutionary Computation, 501–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20520-0_51.
Der volle Inhalt der QuelleHrbek, Václav, und Jan Merta. „Searching the Hyper-heuristic for the Traveling Salesman Problem with Time Windows by Genetic Programming“. In Software Engineering Perspectives in Intelligent Systems, 939–46. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63322-6_81.
Der volle Inhalt der QuelleCazenave, Tristan, und Fabien Teytaud. „Application of the Nested Rollout Policy Adaptation Algorithm to the Traveling Salesman Problem with Time Windows“. In Lecture Notes in Computer Science, 42–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34413-8_4.
Der volle Inhalt der QuelleKuznetsova, Larisa, Arthur Zhigalov, Natalia Yanishevskaya, Denis Parfenov und Irina Bolodurina. „Application of a Modified Ant Colony Imitation Algorithm for the Traveling Salesman Problem with Time Windows When Designing an Intelligent Assistant“. In Advances in Intelligent Systems and Computing, 346–55. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39216-1_31.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Travelling salesman problem with time windows"
Hermes, Zainab, Ashraf O. Nassef und Lotfi K. Gaafar. „Optimal Camera Path Planning for the Inspection of Printed Circuit Boards Using a Two Stepped Optimization Approach“. In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28393.
Der volle Inhalt der QuelleHurkała, Jarosław. „Time-Dependent Traveling Salesman Problem with Multiple Time Windows“. In 2015 Federated Conference on Computer Science and Information Systems. PTI, 2015. http://dx.doi.org/10.15439/2015f311.
Der volle Inhalt der QuelleTomanová, Petra, und Vladimír Holý. „Ant Colony Optimization for Time-Dependent Travelling Salesman Problem“. In ISMSI '20: 2020 4th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3396474.3396485.
Der volle Inhalt der QuelleErol, Mehmet Hamza, und Faruk Bulut. „Real-time application of travelling salesman problem using Google Maps API“. In 2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT). IEEE, 2017. http://dx.doi.org/10.1109/ebbt.2017.7956764.
Der volle Inhalt der QuelleSheng-De Wang und Chii-Ming Tsai. „Hopfield nets with time-varying energy functions for solving the travelling salesman problem“. In 1991 IEEE International Joint Conference on Neural Networks. IEEE, 1991. http://dx.doi.org/10.1109/ijcnn.1991.170500.
Der volle Inhalt der QuelleZhang, Rongkai, Anatolii Prokhorchuk und Justin Dauwels. „Deep Reinforcement Learning for Traveling Salesman Problem with Time Windows and Rejections“. In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. http://dx.doi.org/10.1109/ijcnn48605.2020.9207026.
Der volle Inhalt der QuelleStephens, Shawn S., Ramana V. Grandhi und Donald L. Kunz. „Modified Nonlinear Traveling Salesman Problem with Delivery Time Windows and Item Constraints“. In AIAA Scitech 2020 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2020. http://dx.doi.org/10.2514/6.2020-1088.
Der volle Inhalt der QuelleErdogdu, Kazim, und Korhan Karabulut. „Distance and Energy Consumption Minimization in Electric Traveling Salesman Problem with Time Windows“. In 2020 7th International Conference on Electrical and Electronics Engineering (ICEEE). IEEE, 2020. http://dx.doi.org/10.1109/iceee49618.2020.9102602.
Der volle Inhalt der QuelleNeroni und Tebaldi. „A hybrid heuristic algorithm for solving the Traveling Salesman Problem with Time Windows“. In The 20th International Conference on Modeling & Applied Simulation. CAL-TEK srl, 2021. http://dx.doi.org/10.46354/i3m.2021.mas.001.
Der volle Inhalt der QuelleShi, Xiaohu, Liupu Wang, You Zhou und Yanchun Liang. „An Ant Colony Optimization Method for Prize-collecting Traveling Salesman Problem with Time Windows“. In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.470.
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