Relevant bibliographies by topics / Travelling salesman problem with time windows

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Travelling salesman problem with time windows'

Author: Grafiati
Published: 28 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Travelling salesman problem with time windows"

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Obi, Chris Jojo. "Using genetic algorithm to solve multiple traveling salesman problem and considering Carbon emissions." Indian Journal of Science and Technology 13, no. 36 (September 26, 2020): 3707–15. http://dx.doi.org/10.17485/ijst/v13i36.1316.

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Objectives: The Multiple Travelling Salesman problem is a complex combinatorial optimization problem which is a variance of the Traveling Salesman Problem,where a lot of salesmen are utilized in the solution. In this work a cold chain logistics and route optimization model with minimum transport cost, carbon cost and Refrigeration cost are constructed. Methods: A genetic algorithm is then proposed to solve for the Multiple Travelling Salesman Problem with time windows while transport cost, carbon emission cost and refrigeration cost is minimized. Findings: It was observed that the algorithm evolved towards the direction of the optimal value of the fitness function. Novelty: There are a number of studies that considered tournament selection strategy but just a few have applied genetic algorithm considering insertion method to solve a Multiple Travelling salesman Problem. This study uses insertion method to obtain optimal solution. Also, the researcher considered time windows, transport cost, carbon emission cost and refrigeration cost. Keywords: Genetic algorithm method; cold-logistics; multiple travelling salesman problem
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López-Ibáñez, Manuel, and Christian Blum. "Beam-ACO for the travelling salesman problem with time windows." Computers & Operations Research 37, no. 9 (September 2010): 1570–83. http://dx.doi.org/10.1016/j.cor.2009.11.015.

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Mladenovic, Nenad, Raca Todosijevic, and Dragan Urosevic. "An efficient General Variable Neighborhood Search for large Travelling Salesman Problem with Time Windows." Yugoslav Journal of Operations Research 23, no. 1 (2013): 19–30. http://dx.doi.org/10.2298/yjor120530015m.

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General Variable Neighborhood Search (GVNS) is shown to be a powerful and robust methodology for solving travelling salesman and vehicle routing problems. However, its efficient implementation may play a significant role in solving large size instances. In this paper we suggest new GVNS heuristic for solving Travelling salesman problem with time windows. It uses different set of neighborhoods, new feasibility checking procedure and a more efficient data structure than the recent GVNS method that can be considered as a state-of-the-art heuristic. As a result, our GVNS is much faster and more effective than the previous GVNS. It is able to improve 14 out of 25 best known solutions for large test instances from the literature.
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Tae, Hyun-Chul, and Byung-In Kim. "Dynamic Programming Approach for Prize Colleting Travelling Salesman Problem with Time Windows." IE interfaces 24, no. 2 (June 1, 2011): 112–18. http://dx.doi.org/10.7232/ieif.2011.24.2.112.

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Ascheuer, Norbert, Matteo Fischetti, and Martin Grötschel. "Solving the Asymmetric Travelling Salesman Problem with time windows by branch-and-cut." Mathematical Programming 90, no. 3 (May 2001): 475–506. http://dx.doi.org/10.1007/pl00011432.

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López-Ibáñez, Manuel, Christian Blum, Jeffrey W. Ohlmann, and Barrett W. Thomas. "The travelling salesman problem with time windows: Adapting algorithms from travel-time to makespan optimization." Applied Soft Computing 13, no. 9 (September 2013): 3806–15. http://dx.doi.org/10.1016/j.asoc.2013.05.009.

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Cheng, Chi-Bin, and Chun-Pin Mao. "A modified ant colony system for solving the travelling salesman problem with time windows." Mathematical and Computer Modelling 46, no. 9-10 (November 2007): 1225–35. http://dx.doi.org/10.1016/j.mcm.2006.11.035.

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Hill, Stephen E., and 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, no. 4 (2014): 363. http://dx.doi.org/10.1504/ijiome.2014.067566.

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Budak, Gerçek, and Xin Chen. "Evaluation of the size of time windows for the travelling salesman problem in delivery operations." Complex & Intelligent Systems 6, no. 3 (June 20, 2020): 681–95. http://dx.doi.org/10.1007/s40747-020-00167-y.

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Baltz, Andreas, Mourad El Ouali, Gerold Jäger, Volkmar Sauerland, and 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, no. 4 (April 2015): 615–26. http://dx.doi.org/10.1057/jors.2014.17.

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Dissertations / Theses on the topic "Travelling salesman problem with time windows"

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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.

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This thesis deals with the Travelling salesman problem with time windows. The problem is that the travelling salesman must pass through each defined location exactly once and finally return to the original place for the lowest possible price. The time windows in this problem are that each place can only be visited in a given time range, or it can happen that in a certain period of time there will be no path between some places. The thesis deals with an overview of this problem and problems similar to it. It also deals with the description of various methods by which this problem can be solved. As part of this thesis, an application in the Python programming language was also created, which is used to test selected methods for finding solutions. Finally, the given experiments are evaluated and the effectiveness of the given strategies is compared.
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Ružička, 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.

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This paper deals with optimal distribution issues. One may find listed problems of real life linked to distribution. Moreover, there are explained travelling salesman problem, vehicle routing problem and its variants. This work brings an overview of different ways how to solve vehicle routing problem. In practical part, there is an analysis of distribution of real company. The concept of application is presented in the second part of this paper. This concept could reduce costs of distribution in analyzed company. Testing is aimed mainly on the variant VRPCL (Vehicle Routing Problem with Continuos Loading).
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Asan, N. Evren. "Offline And Online Disk Scheduling Problems." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607909/index.pdf.

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This thesis considers the disk scheduling problem. The problem is investigated in two types of settings: offline and online. We first adopt the traveling salesman problem with time windows in the scheduling literature for solving the offline problem. Then we develop a decision epoch scheme in which offline problems are iteratively used in solving the online problem. We perform an experimental study for our approach and two well-known disk scheduling algorithms, and compare them according to several performance criteria.
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Ptáčková, Michaela. "Optimalizace tras při rozvozu zásilek." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-264544.

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This thesis deals with optimization problems of the parcels distribution. This issue can be solved on the ground of traveling salesman problem whose mathematical and economic model, including their modifications, are presented in the theoretical part of the thesis. We can solve these problems by using exact methods, heuristic and metaheuristic algorithms. In the theoretical part are described traveling salesman problem, traveling salesman problem with time windows, traveling salesman problem with multiple time windows and dynamic traveling salesman problem including possible ways of solution. In the practical part we can find application of problems on the real example, when we are finding the shortest possible route for the PPL's employee under different assumptions. The solution is obtained by using solver Gurobi within the modelling system MPL for Windows. In conclusion of the thesis the results are summarized and models are compared with each other.
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Yuan, 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.

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Dans cette thèse, nous étudions les problèmes de tournées de véhicules dans le contexte de la livraison du dernier kilomètre lorsque plusieurs options de livraisons sont proposées aux clients. Le mode de livraison le plus commun est la livraison à domicile ou au travail. La livraison peut également être effectuée dans des points de collecte tels que des consignes ou des magasins. Ces dernières années, un nouveau concept appelé livraison dans le coffre / dans la voiture a été proposé. Avec ce mode de livraison, les colis des clients peuvent être livrés directement dans les coffres des voitures. Notre objectif est de modéliser et de développer des approches de résolution efficaces pour les problèmes de routage dans ce contexte, dans lequel chaque client peut disposer de plusieurs lieux potentiels de livraison. Premièrement, nous proposons un état de l'art sur les problèmes de routage non-Hamiltoniens. Ensuite, nous étudions le cas avec un seul véhicule, qui est modélisé comme un problème du voyageur de commerce généralisé avec fenêtres de temps (GTSPTW). Quatre formulations en programme linéaire à variables mixtes et un algorithme efficace de branch-and-cut sont proposés. Ensuite, nous étudions le cas multi-véhicules, dénommé problème de tournées de véhicules généralisé avec fenêtres de temps (GVRPTW). Une heuristique efficace basée sur la génération de colonnes est proposée pour le résoudre
In 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
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Mao, Chun-Pin, and 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.

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碩士
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.
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Silva, João Carlos Lopes da. "Planeamento de rotas de distribuição." Master's thesis, 2016. http://hdl.handle.net/10451/24881.

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Tese de mestrado, Estatística e Investigação Operacional, Universidade de Lisboa, Faculdade de Ciências, 2016
Considerando 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.
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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.

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Nous adaptons une heuristique de recherche à voisinage variable pour traiter le problème du voyageur de commerce avec fenêtres de temps (TSPTW) lorsque l'objectif est la minimisation du temps d'arrivée au dépôt de destination. Nous utilisons des méthodes efficientes pour la vérification de la réalisabilité et de la rentabilité d'un mouvement. Nous explorons les voisinages dans des ordres permettant de réduire l'espace de recherche. La méthode résultante est compétitive avec l'état de l'art. Nous améliorons les meilleures solutions connues pour deux classes d'instances et nous fournissons les résultats de plusieurs instances du TSPTW pour la première fois.
We 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.
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Book chapters on the topic "Travelling salesman problem with time windows"

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Qin, Hu, Andrew Lim, and 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.

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Boland, Natashia, Mike Hewitt, Duc Minh Vu, and 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.

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Bar-Yehuda, Reuven, Guy Even, and 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.

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Stützle, Thomas, and 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.

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Tüű-Szabó, Boldizsár, Péter Földesi, and 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.

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Zhang, Yanyan, and 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.

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Rimmel, Arpad, Fabien Teytaud, and 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.

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Hrbek, Václav, and 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.

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Cazenave, Tristan, and 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.

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Kuznetsova, Larisa, Arthur Zhigalov, Natalia Yanishevskaya, Denis Parfenov, and 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.

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Conference papers on the topic "Travelling salesman problem with time windows"

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Hermes, Zainab, Ashraf O. Nassef, and 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.

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Automated Optical Inspection (AOI) systems are rapidly replacing slow and tedious manual inspections of Printed Circuit Boards (PCBs). In an AOI system, a minicamera traverses the PCB in a pre-defined travel path, snapping shots of all the PCB components or nodes, at pre-defined locations. The images are then processed and information about the different nodes is extracted and compared against ideal standards stored in the AOI system. This way, a flawed board is detected. Minimizing both the number of images required to scan all the PCB nodes, and the path through which the camera must travel to achieve this, will minimize the image acquisition time and the traveling time, and thus the overall time of inspection. This consequently both reduces costs and increases production rate. This work breaks down this problem into two sub-problems: The first is a clustering problem; the second a travelling salesman sequencing problem. In the clustering problem, it is required to divide all the nodes of a PCB into the minimum number of clusters. The cluster size is constrained by the given dimensions of the camera’s scope or Field of Vision (FOV). These dimensions determine the dimension of the inspection windows. It is thus required to find the minimum number of inspection windows that will scan all the nodes of a PCB, and their locations. Genetic algorithms are applied in a two-step approach with special operators suited for the problem. A continuous Genetic Algorithm (GA) is applied to find the optimum inspection window locations that cover one node and as many other nodes as possible. A discrete GA is then applied to eliminate redundant inspection windows leaving the minimum number of windows that cover all nodes throughout the PCB. In the second sub-problem, an Ant Colony Optimization (ACO) method is used to find the optimum path between the selected inspection windows. The method proposed in this paper is compared against relevant published work, and it is shown to yield better results.
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Hurkała, 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.

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Tomanová, Petra, and 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.

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Erol, Mehmet Hamza, and 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.

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Sheng-De Wang and 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.

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Zhang, Rongkai, Anatolii Prokhorchuk, and 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.

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Stephens, Shawn S., Ramana V. Grandhi, and 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.

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Erdogdu, Kazim, and 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.

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Neroni and 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.

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Shi, Xiaohu, Liupu Wang, You Zhou, and 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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