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Journal articles on the topic 'Application of travelling salesman problem'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Damithabandara. "An Application to the Travelling Salesman Problem." Operations Research and Applications : An International Journal 4, no. 3/4 (November 30, 2017): 09–20. http://dx.doi.org/10.5121/oraj.2017.4402.

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2

Massinanke, Sambourou, and Chao Zhu Zhang. "Application of Genetic Algorithm on Travelling Salesman Person." Advanced Materials Research 1048 (October 2014): 526–30. http://dx.doi.org/10.4028/www.scientific.net/amr.1048.526.

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GA (Genetic algorithm) is an optimization method based on operators (mutation and crossover) utilizing a survival of the fittest idea. They are utilized favorably in various problems. (TSP) Travelling salesman problem is one of the famous studied. TSP is a permutation problem in which the aim is to determine the shortest tour between n different points (cities), otherwise, the problem aims to find a route covering all cities where that the total distance is minimal. In this study a single salesman travels to each of the cities and close the loop by returning to the city he started, the aim of this study is to determine the minimum number of generations in which salesman does the minimum path, cities are chosen at random as initial population. The new generations are then created iteratively till the proper path is attained.

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3

Singamsetty, Purusotham, and Jayanth Kumar Thenepalle. "An efficient genetic algorithm for solving open multiple travelling salesman problem with load balancing constraint." Decision Science Letters 10, no. 4 (2021): 525–34. http://dx.doi.org/10.5267/j.dsl.2021.5.003.

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The multiple travelling salesman problem (MTSP) is one of the widely studied combinatorial optimization problems with various theoretical and practical applications. However, most of the studies intended to deal with classical MTSP, very limited attention has been given to an open multiple travelling salesman problem and its variants. In this paper, an open multiple travelling salesman problem with load balancing constraint (OMTSPLB) is addressed. The OMTSPLB differs from the conventional MTSP, in which all the salesmen start from the central depot and need not come back to it after visiting the given number of cities by accomplishing the load balance constraint, which helps in fairly distributing the task among all salesmen. The problem aims to minimize the overall traversal distance/cost for operating open tours subject to the load balancing constraint. A zero-one integer linear programming (0-1 ILP) model and an efficient metaheuristic genetic algorithm (GA), is established for the OMTSPLB. Since no existing study on OMTSPLB, the proposed GA is tested on the relaxed version of the present model, comparative results are reported. The comparative results show that the proposed GA is competent over the existing algorithms. Furthermore, extensive experiments are carried out on OMTSPLB and the results show that proposed GA can find the global solution effectively.

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4

Derya, Tusan, Esra Dinler, and Barış Keçeci. "Selective generalized travelling salesman problem." Mathematical and Computer Modelling of Dynamical Systems 26, no. 1 (January 2, 2020): 80–118. http://dx.doi.org/10.1080/13873954.2019.1705496.

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5

Pham, Tu-San, Pieter Leyman, and Patrick De Causmaecker. "The intermittent travelling salesman problem." International Transactions in Operational Research 27, no. 1 (October 30, 2018): 525–48. http://dx.doi.org/10.1111/itor.12609.

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6

CHAN, DONALD, and DANIEL MERCIER. "IC insertion: an application of the travelling salesman problem." International Journal of Production Research 27, no. 10 (October 1989): 1837–41. http://dx.doi.org/10.1080/00207548908942657.

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7

Charon, Irène, and Olivier Hudry. "Application of the noising method to the travelling salesman problem." European Journal of Operational Research 125, no. 2 (September 2000): 266–77. http://dx.doi.org/10.1016/s0377-2217(99)00457-9.

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8

Laporte, Gilbert, Ardavan Asef-Vaziri, and Chelliah Sriskandarajah. "Some Applications of the Generalized Travelling Salesman Problem." Journal of the Operational Research Society 47, no. 12 (December 1996): 1461. http://dx.doi.org/10.2307/3010604.

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9

Laporte, Gilbert, Ardavan Asef-Vaziri, and Chelliah Sriskandarajah. "Some Applications of the Generalized Travelling Salesman Problem." Journal of the Operational Research Society 47, no. 12 (December 1996): 1461–67. http://dx.doi.org/10.1057/jors.1996.190.

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10

Laporte, G., and U. Palekar. "Some applications of the clustered travelling salesman problem." Journal of the Operational Research Society 53, no. 9 (September 2002): 972–76. http://dx.doi.org/10.1057/palgrave.jors.2601420.

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11

CONLEY, WILLIAM. "Travelling salesman problem solved with simulation techniques." International Journal of Systems Science 19, no. 10 (January 1988): 2115–22. http://dx.doi.org/10.1080/00207728808964103.

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12

Kaml, Barraq Subhi, and Mohamed Saad Ibrahim. "Solving the Multi-Objective Travelling Salesman Problem with Real Data Application." Journal of Al-Nahrain University of Science 21, no. 3 (September 1, 2018): 146–61. http://dx.doi.org/10.22401/jnus.21.3.18.

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13

FORT, HUGO, MORDECHAI KORNBLUTH, and FREDY ZYPMAN. "The Travelling Salesman Problem for finite-sized cities." Mathematical Structures in Computer Science 20, no. 6 (November 8, 2010): 1067–78. http://dx.doi.org/10.1017/s096012951000037x.

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We consider a variation of the Travelling Salesman Problem (TSP) in which the cities visited have non-zero spatial extent, in contrast with the classical TSP, which has destinations that are mathematical points. This new approach opens up both new analyses of the problem and new algorithms for solutions, while remaining an economic first approximation to the standard problem. We present one particular solution that, depending on the number and size of the cities, can improve existing algorithms solving the classical TSP.

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14

Benavent, Enrique, Mercedes Landete, Juan-José Salazar-González, and Gregorio Tirado. "The probabilistic pickup-and-delivery travelling salesman problem." Expert Systems with Applications 121 (May 2019): 313–23. http://dx.doi.org/10.1016/j.eswa.2018.12.028.

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15

Sekhar, Tirumalasetti Guna. "An efficient approach for solving Travelling Sales Man Problem." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (August 31, 2021): 2793——2798. http://dx.doi.org/10.22214/ijraset.2021.37838.

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Abstract: Global Position System (GPS) application is quite possibly the most valuable instrument in transportation the executives nowadays. The Roadway transportation is an significant function of GPS. To track down the briefest courses to a spot is the key issue of organization investigation. To address this issue, we have numerous calculations and procedures like Dijkstra algorithm, Ant Colony Optimization, Bellman Portage Algorithm, Floyd-Warshall algorithm, Genetic Algorithm, A* Algorithm furthermore, numerous others. In this paper our fundamental goal is to assess the brute force algorithm and the dynamic programming algorithm in settling the Shortest path issue (The travelling salesman issue). The paper will be finished up by giving the results of time and space complexity of these algorithms. To help a salesman visit every one of the urban communities in the rundown (giving the area of urban areas as the information) and he knows the area of the multitude of urban communities and track down the shortest path with the end goal that he visits every one of the urban areas just a single time and gets back to the city where he begun. The distance (cost) and the relating way ought to be shown as yield.

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16

Hertini, E., J. Nahar, and A. K. Supriatna. "Application of linier fuzzy multi-objective programming model in travelling salesman problem." Journal of Physics: Conference Series 1722 (January 2021): 012036. http://dx.doi.org/10.1088/1742-6596/1722/1/012036.

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17

Hertini, E., J. Nahar, and A. K. Supriatna. "Application of linier fuzzy multi-objective programming model in travelling salesman problem." Journal of Physics: Conference Series 1722 (January 2021): 012036. http://dx.doi.org/10.1088/1742-6596/1722/1/012036.

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18

Grötschel, M., and W. R. Pulleyblank. "Clique Tree Inequalities and the Symmetric Travelling Salesman Problem." Mathematics of Operations Research 11, no. 4 (November 1986): 537–69. http://dx.doi.org/10.1287/moor.11.4.537.

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19

Kovács, László, László Iantovics, and Dimitris Iakovidis. "IntraClusTSP—An Incremental Intra-Cluster Refinement Heuristic Algorithm for Symmetric Travelling Salesman Problem." Symmetry 10, no. 12 (November 22, 2018): 663. http://dx.doi.org/10.3390/sym10120663.

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The Symmetric Traveling Salesman Problem (sTSP) is an intensively studied NP-hard problem. It has many important real-life applications such as logistics, planning, manufacturing of microchips and DNA sequencing. In this paper we propose a cluster level incremental tour construction method called Intra-cluster Refinement Heuristic (IntraClusTSP). The proposed method can be used both to extend the tour with a new node and to improve the existing tour. The refinement step generates a local optimal tour for a cluster of neighbouring nodes and this local optimal tour is then merged into the global optimal tour. Based on the performed evaluation tests the proposed IntraClusTSP method provides an efficient incremental tour generation and it can improve the tour efficiency for every tested state-of-the-art methods including the most efficient Chained Lin-Kernighan refinement algorithm. As an application example, we apply IntraClusTSP to automatically determine the optimal number of clusters in a cluster analysis problem. The standard methods like Silhouette index, Elbow method or Gap statistic method, to estimate the number of clusters support only partitional (single level) clustering, while in many application areas, the hierarchical (multi-level) clustering provides a better clustering model. Our proposed method can discover hierarchical clustering structure and provides an outstanding performance both in accuracy and execution time.

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20

Das, Shila, and Nazimuddin Ahmed. "A Travelling Salesman Problem (TSP) with Multiple Job Facilties." OPSEARCH 38, no. 4 (August 2001): 394–406. http://dx.doi.org/10.1007/bf03398645.

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21

Fosin, Juraj, Davor Davidović, and Tonči Carić. "A GPU Implementation of Local Search Operators for Symmetric Travelling Salesman Problem." PROMET - Traffic&Transportation 25, no. 3 (June 19, 2013): 225–34. http://dx.doi.org/10.7307/ptt.v25i3.300.

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The Travelling Salesman Problem (TSP) is one of the most studied combinatorial optimization problem which is significant in many practical applications in transportation problems. The TSP problem is NP-hard problem and requires large computation power to be solved by the exact algorithms. In the past few years, fast development of general-purpose Graphics Processing Units (GPUs) has brought huge improvement in decreasing the applications’ execution time. In this paper, we implement 2-opt and 3-opt local search operators for solving the TSP on the GPU using CUDA. The novelty presented in this paper is a new parallel iterated local search approach with 2-opt and 3-opt operators for symmetric TSP, optimized for the execution on GPUs. With our implementation large TSP problems (up to 85,900 cities) can be solved using the GPU. We will show that our GPU implementation can be up to 20x faster without losing quality for all TSPlib problems as well as for our CRO TSP problem.

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22

Neuenfeldt Júnior, Alvaro, and Lucas Rebouças Guimarães. "A greedy randomized adaptive search procedure application to solve the travelling salesman problem." International Journal of Industrial Engineering and Management 10, no. 3 (September 30, 2019): 238–42. http://dx.doi.org/10.24867/ijiem-2019-3-243.

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23

Li, Weiqi, and Mingyuan Feng. "Solution attractor of local search in travelling salesman problem: concept, construction and application." International Journal of Metaheuristics 2, no. 3 (2013): 201. http://dx.doi.org/10.1504/ijmheur.2013.056388.

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24

Basu, Sumanta, Megha Sharma, and Partha Sarathi Ghosh. "Efficient preprocessing methods for tabu search: an application on asymmetric travelling salesman problem." INFOR: Information Systems and Operational Research 55, no. 2 (February 7, 2017): 134–58. http://dx.doi.org/10.1080/03155986.2017.1279897.

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25

Zamani, Reza, and Sim Kim Lau. "Embedding learning capability in Lagrangean relaxation: An application to the travelling salesman problem." European Journal of Operational Research 201, no. 1 (February 2010): 82–88. http://dx.doi.org/10.1016/j.ejor.2009.02.008.

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26

Markevich, E. A., and A. S. Trushechkin. "Quantum Branch-and-Bound Algorithm and its Application to the Travelling Salesman Problem." Journal of Mathematical Sciences 241, no. 2 (July 29, 2019): 168–84. http://dx.doi.org/10.1007/s10958-019-04415-6.

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27

Jasim, Sajjad Majeed, and Faez Hassan Ali. "Exact and Local Search Methods for Solving Travelling Salesman Problem with Practical Application." Iraqi Journal of Science 60, no. 5 (May 26, 2019): 1138–53. http://dx.doi.org/10.24996/ijs.2019.60.5.22.

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This paper investigates some exact and local search methods to solve the traveling salesman problem. The Branch and Bound technique (BABT) is proposed, as an exact method, with two models. In addition, the classical Genetic Algorithm (GA) and Simulated Annealing (SA) are discussed and applied as local search methods. To improve the performance of GA we propose two kinds of improvements for GA; the first is called improved GA (IGA) and the second is Hybrid GA (HGA). The IGA gives best results than GA and SA, while the HGA is the best local search method for all within a reasonable time for 5 â‰¤ n â‰¤ 2000, where n is the number of visited cities. An effective method of reducing the size of the TSP matrix was proposed with the existence of successive rules. The problem of the total cost of Iraqi cities was also discussed and solved by some methods in addition to local search methods to obtain the optimal solution.

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28

Tesfaldet, Bereket T., and Augusto Y. Hermosilla. "A Lamarckian Genetic Algorithm Applied to the Travelling Salesman Problem." Advances in Complex Systems 02, no. 04 (December 1999): 431–57. http://dx.doi.org/10.1142/s0219525999000229.

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Genetic Algorithms (GAs) comprise a class of adaptive heuristic search methods analogous to genetic inheritance and Darwinian strife for survivial of individuals within a population. Today, GAs are widely used to solve complex optimization problems, including ill-conditioned and NP-complete types arising in business, commerce, engineering, large-scale industries, and many other areas. To address these wide areas of applications and to improve upon their drawbacks, many variations and modifications of GAs have been proposed. The GA variation proposed in this paper has four basic operators: reproduction, recombination and two mutation operators, particularly applied to the famous and extensively studied Traveling Salesman Problem (TSP) in large-scale combinatorial optimization. Three of the operators use diversity information (standard deviation of costs) from the current population to adjust the diversity of the next population. The fourth one is an introduced new mutation operator called p-displacement that simulates the Lamarckian evolutionary learning and training concepts of gene improvement to bring chromosomes to their local optimum. We call the proposed GA: Lamarckian Genetic Algorithm-Traveling Salesman Problem (LGA-TSP). Emprical results show performance improvements compared to the classic and other modified GAs, as well as simulated annealing.

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29

Wołoszyn, Paweł. "Image Segmentation and Object Counting as an Instance of Travelling Salesman Problem." Image Processing & Communications 19, no. 2-3 (September 1, 2014): 59–70. http://dx.doi.org/10.1515/ipc-2015-0011.

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Abstract The goal of this paper is to evaluate possible application of travelling salesman problem and its solving methods to image segmentation and object counting. This approach is inspired both by human skill of subitization and by ability of biological systems to solve optimization problems. Subitizing, or the ability to determine a number of objects without counting them, can be treated as a special case of image processing focused on extracting objects from background and enumerating them. This paper describes a method of generating linear image profile based on simple graph representation in which an optimal or suboptimal cycle is sought. Segmentation and counting can be then carried out by dividing the profile into coherent segments.

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30

Wang, Peng, Cesar Sanin, and Edward Szczerbicki. "Evolutionary algorithm and decisional DNA for multiple travelling salesman problem." Neurocomputing 150 (February 2015): 50–57. http://dx.doi.org/10.1016/j.neucom.2014.01.075.

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31

Yousefikhoshbakht, Majid, and Mohammad Sedighpour. "New Imperialist Competitive Algorithm to solve the travelling salesman problem." International Journal of Computer Mathematics 90, no. 7 (July 2013): 1495–505. http://dx.doi.org/10.1080/00207160.2012.758362.

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32

Grötschel, M., and W. R. Pulleyblank. "Corrigenda: Clique Tree Inequalities and the Symmetric Travelling Salesman Problem." Mathematics of Operations Research 12, no. 1 (February 1987): 182–84. http://dx.doi.org/10.1287/moor.12.1.182.

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33

Aras, N., B. J. Oommen, and İ. K. Altınel. "The Kohonen network incorporating explicit statistics and its application to the travelling salesman problem." Neural Networks 12, no. 9 (November 1999): 1273–84. http://dx.doi.org/10.1016/s0893-6080(99)00063-5.

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34

Kucukoglu, Ilker, Tulin Gunduz, Fatma Balkancioglu, Emine Chousein Topal, and Oznur Sayim. "Application of precedence constrained travelling salesman problem model for tool path optimization in CNC milling machines." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 9, no. 3 (May 28, 2019): 59–68. http://dx.doi.org/10.11121/ijocta.01.2019.00662.

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In this study, a tool path optimization problem in Computer Numerical Control (CNC) milling machines is considered to increase the operational efficiency rates of a company. In this context, tool path optimization problem of the company is formulated based on the precedence constrained travelling salesman problem (PCTSP), where the general form of the TSP model is extended by taking the precedence of the tool operations into account. The objective of the model is to minimize total idle and unnecessary times of the tools for internal operations. To solve the considered problem, a recent optimization algorithm, called Satin Bowerbird Optimizer (SBO), is used. Since the SBO is first introduced for the global optimization problems, the original version of the SBO is modified for the PCTSP with discretization and local search procedures. In computational studies, first, the performance of the proposed algorithm is tested on a well-known PCTSP benchmark problems by comparing the proposed algorithm against two recently proposed meta-heuristic approaches. Results of the comparisons show that the proposed algorithm outperforms the other two competitive algorithms by finding better results. Then, the proposed algorithm is carried out to optimize the hole drilling processes of three different products produced by the company. For this case, with up to 4.05% improvement on the operational times was provided for the real-life problem of the company. As a consequence, it should be noted that the proposed solution approach for the tool path optimization is capable of providing considerable time reductions on the CNC internal operations for the company.

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35

dell'Amico, M., F. Maffioli, and P. Varbrand. "On Prize-collecting Tours and the Asymmetric Travelling Salesman Problem." International Transactions in Operational Research 2, no. 3 (July 1995): 297–308. http://dx.doi.org/10.1111/j.1475-3995.1995.tb00023.x.

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36

GERACE, IVAN, and FEDERICO GRECO. "The Travelling Salesman Problem in symmetric circulant matrices with two stripes." Mathematical Structures in Computer Science 18, no. 1 (February 2008): 165–75. http://dx.doi.org/10.1017/s0960129508006609.

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The Symmetric Circulant Travelling Salesman Problem asks for the minimum cost tour in a symmetric circulant matrix. The computational complexity of this problem is not known – only upper and lower bounds have been determined. This paper provides a characterisation of the two-stripe case. Instances where the minimum cost of a tour is equal to either the upper or lower bound are recognised. A new construction providing a tour is proposed for the remaining instances, and this leads to a new upper bound that is closer than the previous one.

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37

Tannady, Hendy, and Andrew Verrayo Limas. "Perancangan Aplikasi Penjadwalan Traveling Salesman Problem dengan Algoritma Genetika." ComTech: Computer, Mathematics and Engineering Applications 3, no. 2 (December 1, 2012): 977. http://dx.doi.org/10.21512/comtech.v3i2.2332.

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Supply chain management plays an important role in enhancing the efficiency and effectiveness of manufacturing industry business process. In this research, the problem is taken from a sales division in a company in determining the optimal sequence when delivering goods into nine cities. This problem is oftenreferred as travelling salesman problem. This problem is considered important since the optimal sequence can cut off operational cost. Creating an artificial intelligence for the company in determining the location and the optimal sequence of delivering goods is the main objective of this research. A genetic algorithm is utilized to determine the location and the optimal sequence. While for processing the data and concluding the result, researcher designed a Java-based application that provides the capability of automatic computing. The result of this computation is a sequence of locations with a fitness number for each. The best fitness number for the sequence location will be used for the final result and the conclusion to answer the company’s problem.

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38

Wang, Yong, and Yiwen Wu. "Frequency Graphs for Travelling Salesman Problem Based on Ant Colony Optimization." International Journal of Computational Intelligence and Applications 18, no. 03 (September 2019): 1950016. http://dx.doi.org/10.1142/s1469026819500160.

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Traveling salesman problem (TSP) is a typical combinatorial optimization problem. A heuristic model called frequency graph is introduced for TSP. It is computed with a set of optimal i-vertex paths (OP) in a weighted graph. The frequencies on the edges are enumerated from the set of OPs. The OPs have more intersections of edges with the optimal Hamiltonian cycle (OHC) than they do with the other Hamiltonian cycles. Thus, the frequencies of the OHC edges are generally bigger than those of most of the other edges. They are taken as the heuristic information instead of edges’ weights for TSP. The ant colony optimization is used to find an approximation or OHC based on the frequency graph. The solutions are compared with those using weighted graphs for certain TSP instances. The experimental results show that the frequency graph is better than weighted graph (WG) for most TSPs under the same preconditions.

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39

Bachmann, Florian, Helmut Schaeben, and Ralf Hielscher. "Optimizing the experimental design of texture goniometry." Journal of Applied Crystallography 45, no. 6 (November 15, 2012): 1173–81. http://dx.doi.org/10.1107/s0021889812041611.

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Pole figure measurements with an X-ray texture goniometer equipped with a point detector are rather time consuming: depending on the angular resolution to be recorded, of the order of several hours per pole figure. Conventionally, the pole hemisphere is scanned along latitudinal small circles according to a regular grid of constant step sizes in both the azimuthal and the polar angle. In the case of sharp textures an adaptive successive local refinement strategy of the pole hemisphere may offer a better performance in less time. Then the measurement positions of the grid are highly irregularly distributed over the pole hemisphere. To avoid erratic movements when turning the specimen, the scanning order is optimized by means of resolving a travelling salesman problem such that the total travelling time is minimized. Several algorithms are described resolving the travelling salesman problem with respect to the irregular grid to be applied for each pole figure and for each step of successive refinement. A practical application to pole figure measurements exposes total savings of about 1/8 compared to the conventional scanning order. Successive local refinement of the experimental design and optimization of the order of its measurement positions are well suited to the purpose of controlling a texture goniometer.

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40

Resende Lima, Victor Hugo, Elias De Oliveira Lima, and Hassan Sherafat. "Roteirization of vehicles in the delivery/collection problems - Application of a modifed Ant Colony Algorithm." Revista Brasileira de Computação Aplicada 12, no. 1 (March 23, 2020): 44–53. http://dx.doi.org/10.5335/rbca.v12i1.9317.

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Delivering and collecting problems concern to situations where goods are delivered (or collected) in practical cases. For example, solid waste collection, postal services and snow removing. It can be modelled as the well-known Chinese Postman Problem on mixed graphs (MCPP). The MCPP is a fair model for the delivering and collecting problem because its goal is to cover all links of a mixed graph with minimal cost. The objective of this paper is to develop an algorithm based on Ant Colony Optimization and apply it to MCPP solution. The MCPP is initially converted into an equivalent Travelling Salesman Problem (TSP) and then tackled on this second instance. The results were promising and comparable to some other algorithms. It was found results near of optimal solutions in some cases.

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41

Kralev, Velin. "Different Applications of the Genetic Mutation Operator for Symetric Travelling Salesman Problem." International Journal on Advanced Science, Engineering and Information Technology 8, no. 3 (June 8, 2018): 762. http://dx.doi.org/10.18517/ijaseit.8.3.4867.

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42

Verma, Madhushi, and K. K. Shukla. "Application of Fuzzy Optimization to the Orienteering Problem." Advances in Fuzzy Systems 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/569248.

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This paper deals with the orienteering problem (OP) which is a combination of two well-known problems (i.e., travelling salesman problem and the knapsack problem). OP is an NP-hard problem and is useful in appropriately modeling several challenging applications. As the parameters involved in these applications cannot be measured precisely, depicting them using crisp numbers is unrealistic. Further, the decision maker may be satisfied with graded satisfaction levels of solutions, which cannot be formulated using a crisp program. To deal with the above-stated two issues, we formulate thefuzzyorienteering problem (FOP) and provide a method to solve it. Here we state the two necessary conditions of OP of maximizing the total collected score and minimizing the time taken to traverse a path (within the specified time bound) as fuzzy goals and the remaining necessary conditions as crisp constraints. Using the max-min formulation of the fuzzy sets obtained from the fuzzy goals, we calculate the fuzzy decision sets (ZandZ∗) that contain the feasible paths and the desirable paths, respectively, along with the degrees to which they are acceptable. To efficiently solve large instances of FOP, we also present a parallel algorithm on CREW PRAM model.

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43

N. P, Akpan,, and Onyebuchi, U.R. "An Application of Metric Method of Solving Travelling Salesman Routing Problem to Table Water Company." IOSR Journal of Mathematics 12, no. 04 (April 2016): 115–23. http://dx.doi.org/10.9790/5728-120402115123.

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44

Favata, F., and R. Walker. "A study of the application of Kohonen-type neural networks to the Travelling Salesman Problem." Biological Cybernetics 64, no. 6 (April 1991): 463–68. http://dx.doi.org/10.1007/bf00202610.

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45

Woods, Brad D., and Abraham P. Punnen. "A class of exponential neighbourhoods for the quadratic travelling salesman problem." Journal of Combinatorial Optimization 40, no. 2 (June 2, 2020): 303–32. http://dx.doi.org/10.1007/s10878-020-00588-y.

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46

Boryczka, Urszula, and Krzysztof Szwarc. "An effective hybrid harmony search for the asymmetric travelling salesman problem." Engineering Optimization 52, no. 2 (March 25, 2019): 218–34. http://dx.doi.org/10.1080/0305215x.2019.1579804.

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Paydar, Mohammad Mahdi, Iraj Mahdavi, and Kathryn A. Szabat. "Application of single depot multiple travelling salesman method to cell formation problems." International Journal of Applied Decision Sciences 3, no. 4 (2010): 390. http://dx.doi.org/10.1504/ijads.2010.036853.

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Mak, V., and N. Boland. "Heuristic approaches to the asymmetric travelling salesman problem with replenishment arcs." International Transactions in Operational Research 7, no. 4-5 (September 2000): 431–47. http://dx.doi.org/10.1111/j.1475-3995.2000.tb00209.x.

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Samah, K. A. F. A., N. Sabri, R. Hamzah, R. Roslan, N. A. Mangshor, and A. A. M. Asri. "Brute force algorithm implementation for traveljoy travelling recommendation system." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 2 (November 1, 2019): 1042. http://dx.doi.org/10.11591/ijeecs.v16.i2.pp1042-1049.

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<span>This paper presents the Brute Force algorithm implementation for TravelJoy Travelling Recommendation System. Due to overwhelmed information in the internet, travelers faced difficulties in finding and comparing which places in Melaka that worth to visit. Melaka is a well-known place as one of the most popular tourist spots in Malaysia, famous with historical places. All the mentioned problems were time-consuming and required lots of efforts for manual comparison between places and planning the trip itinerary. An efficient application system is needed to assist travelers in planning their trip itinerary by providing details of interesting place in Melaka, budget estimating and recommendation of sequence places which to visit. The TravelJoy application applied Traveling Salesman Problem (TSP) concept using Brute Force algorithm in determining the least time duration for the selected places and adapting Expected Time Arrival (ETA). It was found through Brute Force algorithm adaptation; the recommendation system is reliable based on the functional and reliability testing with t-test result of 0.00067, indicates the system is accepted.</span>

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Xu, Xiaolong, Hao Yuan, Peter Matthew, Jeffrey Ray, Ovidiu Bagdasar, and Marcello Trovati. "GORTS: genetic algorithm based on one-by-one revision of two sides for dynamic travelling salesman problems." Soft Computing 24, no. 10 (September 21, 2019): 7197–210. http://dx.doi.org/10.1007/s00500-019-04335-2.

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Abstract The dynamic travelling salesman problem (DTSP) is a natural extension of the standard travelling salesman problem, and it has attracted significant interest in recent years due to is practical applications. In this article, we propose an efficient solution for DTSP, based on a genetic algorithm (GA), and on the one-by-one revision of two sides (GORTS). More specifically, GORTS combines the global search ability of GA with the fast convergence feature of the method of one-by-one revision of two sides, in order to find the optimal solution in a short time. An experimental platform was designed to evaluate the performance of GORTS with TSPLIB. The experimental results show that the efficiency of GORTS compares favourably against other popular heuristic algorithms for DTSP. In particular, a prototype logistics system based on GORTS for a supermarket with an online map was designed and implemented. It was shown that this can provide optimised goods distribution routes for delivery staff, while considering real-time traffic information.

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