Relevant bibliographies by topics / TSPLIB

Contents

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

Academic literature on the topic 'TSPLIB'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "TSPLIB"

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Reinelt, Gerhard. "TSPLIB—A Traveling Salesman Problem Library." ORSA Journal on Computing 3, no. 4 (1991): 376–84. http://dx.doi.org/10.1287/ijoc.3.4.376.

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Yun, Ho-Yoeng, Suk-Jae Jeong, and Kyung-Sup Kim. "Advanced Harmony Search with Ant Colony Optimization for Solving the Traveling Salesman Problem." Journal of Applied Mathematics 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/123738.

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We propose a novel heuristic algorithm based on the methods of advanced Harmony Search and Ant Colony Optimization (AHS-ACO) to effectively solve the Traveling Salesman Problem (TSP). The TSP, in general, is well known as an NP-complete problem, whose computational complexity increases exponentially by increasing the number of cities. In our algorithm, Ant Colony Optimization (ACO) is used to search the local optimum in the solution space, followed by the use of the Harmony Search to escape the local optimum determined by the ACO and to move towards a global optimum. Experiments were performed
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Karagul, Kenan, Erdal Aydemir, and Sezai Tokat. "Using 2-Opt based evolution strategy for travelling salesman problem." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 6, no. 2 (2016): 103–13. http://dx.doi.org/10.11121/ijocta.01.2016.00268.

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Harmony search algorithm that matches the (µ+1) evolution strategy, is a heuristic method simulated by the process of music improvisation. In this paper, a harmony search algorithm is directly used for the travelling salesman problem. Instead of conventional selection operators such as roulette wheel, the transformation of real number values of harmony search algorithm to order index of vertex representation and improvement of solutions are obtained by using the 2-Opt local search algorithm. Then, the obtained algorithm is tested on two different parameter groups of TSPLIB. The proposed method
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Veeresh, M., T. Jayanth Kumar, and M. Thangaraj. "Solving the single depot open close multiple travelling salesman problem through a multi-chromosome based genetic algorithm." Decision Science Letters 13, no. 2 (2024): 401–14. http://dx.doi.org/10.5267/j.dsl.2024.1.006.

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The multiple travelling salesman problem (MTSP) extends the classical travelling salesman problem (TSP) by involving multiple salesman in the solution. MTSP has found widespread applications in various domains, such as transportation, robotics, and networking. Despite extensive research on MTSP and its variants, there has been limited attention given to the open close multiple travelling salesman problem (OCMTSP) and its variants in the literature. To the best of the author's knowledge, only one study has addressed OCMTSP, introducing an exact algorithm designed for optimal solutions. However,
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Ahmed, Zakir Hussain. "The Ordered Clustered Travelling Salesman Problem: A Hybrid Genetic Algorithm." Scientific World Journal 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/258207.

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The ordered clustered travelling salesman problem is a variation of the usual travelling salesman problem in which a set of vertices (except the starting vertex) of the network is divided into some prespecified clusters. The objective is to find the least cost Hamiltonian tour in which vertices of any cluster are visited contiguously and the clusters are visited in the prespecified order. The problem is NP-hard, and it arises in practical transportation and sequencing problems. This paper develops a hybrid genetic algorithm using sequential constructive crossover, 2-opt search, and a local sea
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Zhang, Jing Min, and Cong Cong Wu. "Improved Shuffled Frog-Leaping Algorithm and its Application." Applied Mechanics and Materials 155-156 (February 2012): 92–96. http://dx.doi.org/10.4028/www.scientific.net/amm.155-156.92.

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This paper proposes an improved shuffled frog-leaping algorithm, the algorithm improves the subpopulation frog individual optimization way which is not just the worst individual optimization. "Guide optimal" probability and "guide suboptimal" probability are put forward. The experiments results of multiple problems of the TSPLIB show that the algorithm is feasible and effective.
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Thirugnanasambandam, Kalaipriyan, Raghav R.S, Saravanan D, Prabu U, and Rajeswari M. "Experimental Analysis of Ant System on Travelling Salesman Problem Dataset TSPLIB." EAI Endorsed Transactions on Pervasive Health and Technology 5, no. 19 (2019): 163092. http://dx.doi.org/10.4108/eai.13-7-2018.163092.

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Ismail, A. H., N. Hartono, S. Zeybek, and D. T. Pham. "Using the Bees Algorithm to solve combinatorial optimisation problems for TSPLIB." IOP Conference Series: Materials Science and Engineering 847 (May 28, 2020): 012027. http://dx.doi.org/10.1088/1757-899x/847/1/012027.

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Liu, Ping, and Yue Guang Li. "An Improve Firefly Algorithm and its Application." Applied Mechanics and Materials 404 (September 2013): 533–37. http://dx.doi.org/10.4028/www.scientific.net/amm.404.533.

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In this paper, according to the characteristics of TSP. A Novel Firefly Algorithm was used to solve the TSP, the algorithm was experimented and the experimental results show that the new algorithm to be successful in locating multiple solutions and better accuracy. The experimental result demonstrates that the Improve firefly algorithm can get better solutions to some Traveling Salesman Problems (TSP) than the solutions given in TSPLIB.
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Nanda Ginting, Subhan Hafiz, and Mayang Mughnyanti. "The Utilization Of The Simple Multi Attribute Rating Exploiting Ranks Can Enhance The Performance Of The Aco Algorithm." Jurnal Minfo Polgan 12, no. 1 (2023): 1325–29. http://dx.doi.org/10.33395/jmp.v12i1.12743.

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In a comparative study, the performance of the ACO algorithm and a modified genetic algorithm (MGA) were evaluated for solving the multiple salesman traveling problem (MTSP) using various datasets from TSPLIB. The results revealed that although the proposed algorithm did not achieve the best solution, it exhibited improved time efficiency as the dataset size increased. The objective of this study is to improve the performance of the ACO algorithm by integrating the SMARTER algorithm, which aims to find the optimal route and minimize travel time. The combination of these algorithms offers alter
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Dissertations / Theses on the topic "TSPLIB"

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Humpherys, Brian. "SIGNAL TDOA BASED HIGH RESOLUTION TSPI." International Foundation for Telemetering, 1994. http://hdl.handle.net/10150/608843.

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International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and Conference Center, San Diego, California<br>This paper describes a method for determining high resolution time, space, and position information for a test range flight vehicle using four tracking receivers. Equipped with GPS time systems, each receiver records the exact time at which a time marker embedded in the transmitted TM data stream is received. With this information, the time difference of arrival for the time markers at three of the receivers can be calculated referenced to the four
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Reed, Gary. "TSPI DATA PROCESSING IN THE TELEMETRY ENVIRONMENT." International Foundation for Telemetering, 1985. http://hdl.handle.net/10150/615725.

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International Telemetering Conference Proceedings / October 28-31, 1985 / Riviera Hotel, Las Vegas, Nevada<br>Most test ranges are required to process both telemetry and Time Space Position Information (TSPI) data in real time. Using the Integrated Flight Data Processing System (IFDAPS) at Edwards AFB as an example, this paper identifies some of the basic differences between telemetry and TSPI data processing and discusses methods of integrating the two types of processing. Included for consideration in the integrated processing are data acquisition, measurement displays, recording, derived me
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Wright, Rob, and Mike Paulick. "A SYSTEM ARCHITECTURE FOR THE DISTRIBUTION OF REAL-TIME TSPI." International Foundation for Telemetering, 2000. http://hdl.handle.net/10150/606487.

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International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California<br>The Range Instrumentation and Control System (RICS) is the twenty-first century replacement for an aging time-space-position information (TSPI) distribution and collection system used by the 46th Test Wing at Eglin AFB, Florida. The purpose of the RICS is to collect TSPI and distribute it across a wide area network in real-time. It will utilize a multi-threaded C++ program on VxWorks (a real-time operating system by Wind River Systems) to acquire TS
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Paulick, Mike, and Tim Thomas. "AN OBJECT-ORIENTED PC-BASED SYSTEM FOR TSPI COLLECTION AND DISTRIBUTION." International Foundation for Telemetering, 2001. http://hdl.handle.net/10150/607577.

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International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada<br>The Range Instrumentation and Control System (RICS) is a PC-based client/server application designed to collect time-space position information (TSPI) from remote radar test sites and distribute it in real-time across a wide area network (WAN). The system architecture is composed of two main parts - the Data Interface Adapter (or DIA, which runs under VxWorks and is implemented using C/C++) and the RICS console PC (which runs under Windows 2000 and is implemented
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Kujiraoka, Scott R., and Russell G. Fielder. "Using GPS for TSPI and Flight Termination Capabilities of a Missile Telemetry Section." International Foundation for Telemetering, 2005. http://hdl.handle.net/10150/605058.

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ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada<br>The Joint Advanced Missile Instrumentation (JAMI) Program involves the integration of Global Positioning System (GPS) tracking technology into the Test Ranges. GPS Technology will be used for Time, Space, and Position Information (TSPI) as well as Flight Termination purposes. JAMI is currently developing the JAMI TSPI Unit (JTU) and the Flight Termination Safe & Arm (FTS&A) devices. This paper
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James, Russell W., and James C. Bevier. "ACQUISITION AND DISTRIBUTION OF TSPI DATA USING COTS HARDWARE OVER AN ETHERNET NETWORK." International Foundation for Telemetering, 2003. http://hdl.handle.net/10150/607477.

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International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada<br>The Western Aeronautical Test Range (WATR) operates the ground stations for research vehicles operating at the NASA Dryden Flight Research Center (DFRC). Recently, the WATR implemented a new system for distributing Time, Space, and Position Information (TSPI) data. The previous system for processing this data was built on archaic hardware that is no longer supported, running legacy software with no upgrade path. The purpose of the Radar Information Processing Syst
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Snider, Christopher W. "A PROGRAMMATIC OVERVIEW OF THE DEVELOPMENT AND IMPLEMENTATION OF THE RICS." International Foundation for Telemetering, 2001. http://hdl.handle.net/10150/606431.

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International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada<br>The Range Instrumentation and Control System (RICS) is a network of personal computers (PCs), routers, and switches designed to transport time-space-position information (TSPI) and/or other data between multiple Test Sites and data reduction facilities. The typical use of RICS will be the transport of TSPI data from a System Under Test (SUT) to a Focus Site for real-time display and post-mission analysis of the data. This capability will be expanded to includ
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Sternke, Barry, and Matthew Ray. "TSPI Radar Methodologies for Improved Positional Performance/Accuracy of C-Band Auto-tracking Telemetry." International Foundation for Telemetering, 2013. http://hdl.handle.net/10150/579572.

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Switzer, Earl R., John Wrin, and James Huynh. "COMBINING TECHNOLOGIES TO FOSTER IMPROVED TSPI ACCURACY AND INCREASE SHARING OF THE FREQUENCY SPECTRUM." International Foundation for Telemetering, 1999. http://hdl.handle.net/10150/608757.

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International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada<br>The loss of radio frequency (RF) spectrum for use in testing has steadily increased the likelihood that users of the few remaining frequencies available to test ranges will experience scheduling conflicts and interference with nontest users. A gradual increase in the base of test customers engaged in scientific, military, and commercial R&D, point toward a near term situation in which more test customers will be competing for fewer frequencies. The test ranges, of
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Hoefener, Carl E., and Dennis Beech. "GPS Provides a Flexible Tool for TSPI Regardless of Type of Vehicle Being Tested." International Foundation for Telemetering, 1989. http://hdl.handle.net/10150/614703.

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International Telemetering Conference Proceedings / October 30-November 02, 1989 / Town & Country Hotel & Convention Center, San Diego, California<br>The test scenarios of vehicles under test vary greatly depending upon the type of vehicle being tested. This paper will examine the test characteristics of a variety of vehicles and the TSPI requirements of each. The types of platforms to be investigated range from soldiers, jeeps, tanks, helicopters and high performance aircraft to ballistic missiles, air-air, air-ground and ground-air missiles in addition to space vehicles. Each of these platfo
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Book chapters on the topic "TSPLIB"

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Mejia, Jezreel, Andrés Garcia, and Mirna A. Muñoz. "TSPi to Manage Software Projects in Outsourcing Environments." In Advances in Intelligent Systems and Computing. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36981-0_38.

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Caballero, Edgar, Jose A. Calvo-Manzano, Gonzalo Cuevas, and Tomás San Feliu. "Implementation of Software Process Improvement through TSPi in Very Small Enterprises." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15666-3_25.

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Zhang Liyi, Li Hongbo, Fei Teng, and Pan Xuhua. "Improved Bee Colony Optimization for Traveling Salesman Problem." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2018. https://doi.org/10.3233/978-1-61499-927-0-771.

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An improved artificial bee colony algorithm is proposed for traveling salesman problem, which is a classical NP- hard problem. By improved artificial bee colony algorithm we introduce swarm behavior of the artificial fish swarm algorithm and the crossover operator of the genetic algorithm, and enlightens the underdamping motion of physics which uses it to adaptively update for the visual range of the artificial fish swarm algorithm. Through the simulation of six classic traveling salesman problems in the TSPLIB standard library and comparison with other improved algorithms, we show that the im
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Wang Yong, Geng Chang Xin, and Wu Yi Wen. "A Heuristic Algorithm to Eliminate Edges for TSP." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2018. https://doi.org/10.3233/978-1-61499-927-0-231.

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A heuristic algorithm is provided to trim many edges for reducing the search space of traveling salesman problem (TSP). The heuristic algorithm is designed according to a probability model and the fuzzy numbers plays an important role to enhance the performance. The heuristic algorithm may lose a few edges in some optimal solutions if the parameter N is too small or F is too big in the algorithm. Since we are not sure whether all optimal solutions in the original graph are trimmed, the best and worst solutions in the preserved graphs are not proven. The experimental results demonstrate that th
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Avşar Bihter, Esmaeili Aliabadi Danial, and Esmaeili Aliabadi Edris. "TSP Solver: An Integrated Framework for Solving Traveling Salesman Problems Consistent with TSPLIB." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-828-0-70.

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The Traveling Salesman Problem (TSP) is the subject of study in operational research for more than 30 years. The TSP is considered as NP-complete; consequently, many heuristic and metaheuristic algorithms have been developed to cope with the intractable nature of the problem. Although the problem is well-studied, lack of integrated software that harnesses the new computers' computational power and provides an easy comparison between heuristic algorithms is sensible. TSP solver is the state-of-the-art software that provides a common framework to compare the performance of different algorithms o
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Quispe, Gloria Lola, Maria Fernanda Rodríguez, and José Daniel Ontiveros. "Comparative Analysis of ACO Algorithms for the Solution of the Travelling Salesman Problem." In Handbook of Research on Software Quality Innovation in Interactive Systems. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7010-4.ch014.

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Metaheuristics are non-deterministic algorithms. Metaheuristic strategies are related to design. This chapter presents an introduction on metaheuristics, from the point of view of its theoretical study and the foundations for its use. Likewise, a description and comparative study of the ant colony-based algorithms is carried out. These are ant system (AS), ant colony system (ACS), and max-min ant system (MMAS). These results serve to deliver solutions to complex problems and generally with a high degree of combinatorics for those there is no way to find the best reasonable time. An experimenta
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Paul, Victer, Ganeshkumar C, and Jayakumar L. "Performance Evaluation of Population Seeding Techniques of Permutation-Coded GA Traveling Salesman Problems Based Assessment." In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8048-6.ch053.

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Genetic algorithms (GAs) are a population-based meta-heuristic global optimization technique for dealing with complex problems with a very large search space. The population initialization is a crucial task in GAs because it plays a vital role in the convergence speed, problem search space exploration, and also the quality of the final optimal solution. Though the importance of deciding problem-specific population initialization in GA is widely recognized, it is hardly addressed in the literature. In this article, different population seeding techniques for permutation-coded genetic algorithms
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Conference papers on the topic "TSPLIB"

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Kupferschmidt, B., and R. Docimo. "A3.1 - High-Accuracy Time Space Position Information (TSPI) - Field Test Results." In ETTC 2024 - European Test and Telemetry Conference. AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, 2024. https://doi.org/10.5162/ettc2024/a3.1.

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Rios, Brenner H. O., Eduardo C. Xavier, Flávio K. Miyazawa, and Pedro Amorim. "Stochastic multi-depot capacitated vehicle routing problem with pickup and delivery: heuristic approaches." In Encontro de Teoria da Computação. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/etc.2021.16388.

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We present a natural probabilistic variation of the multi-depot vehicle routing problem with pickup and delivery. We denote this variation by Stochastic multi-depot capacitated vehicle routing problem with pickup and delivery (SMCVRPPD). We present an algorithm to compute the expected length of an apriori route under general probabilistic assumptions. To solve the SMCVRPPD we propose an Iterated Local Search (ILS) and a Variable Neighborhood Search(VNS). We evaluate the performance of these heuristics on a data set adapted from TSPLIB instances. The results show that the ILS is effective to so
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C. Ottoni, André Luiz, Marcos S. de Oliveira, Daniela C. R. de Oliveira, and Erivelton G. Nepomuceno. "Transferência de Aprendizado por Reforçoo em Problemas de Otimização Combinatória." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1098.

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O Aprendizado por Reforço (AR) é uma técnica de Machine Learning com importantes aplicações em problemas de otimização combinatória. No entanto, a literatura carece de estudos sobre a transferência de AR entre domínios de otimização. Baseando-se nisso, o objetivo deste trabalho foi aplicar e analisar a transferência de conhecimento do AR entre o Problema do Caixeiro Viajante (TSP) e o Sequential Ordering Problem (SOP). Para isso, foi adotada a biblioteca de instâncias TSPLIB e o algoritmo SARSA. A metodologia proposta compreende: modelagem do sistema de AR, geração da base de conhecimento (QTS
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T. Cordeiro Ottoni, Lara, and Lucas S. Batista. "Proposta de uma abordagem multiobjetivo para o projeto de dimensionamento de redes de gás natural." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1191.

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O gás natural vem sendo usado de modo crescente como fonte de energia e se apresenta como uma forte tendência para o futuro. Nesse contexto, levando-se em consideração o alto custo de instalação de gasodutos, o projeto dessas redes requer soluções de qualidade, relacionando não apenas indicadores financeiros mas também de confiabilidade e segurança quanto ao atendimento da demanda. Assume-se uma topologia de rede pré-definida, onde os diâmetros das tubulações definem as variáveis de projeto. Propõe-se algoritmos multiobjetivo baseados na metaheurística Multiobjetive Variable Neiborhood Search
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T. Cordeiro Ottoni, Lara, André Luiz C. Ottoni, Marcos S. de Oliveira, and Erivelton G. Nepomuceno. "AutoRL-TSP: Sistema de Aprendizado por Reforço Automatizado para o Problema do Caixeiro Viajante." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1658.

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O AutoML (Aprendizado de Máquina Automatizado) tem como objetivo desenvolver técnicas para automatizar todo o processo de aprendizagem de máquina, de forma a obter um sistema que se adeque as condições do problema. Nesse sentido, um dos aspectos relevantes de sistemas de AutoML é a definição das configurações iniciais da simulação, que podem influenciar consideravelmente no resultado final do aprendizado. No entanto, a literatura carece de trabalhos que apresentem métodos de AutoML para aplicações de Aprendizado por Reforço (AR) em problemas de otimização combinatória. Dessa forma, o objetivo
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SALES, RAVELLY OLIVEIRA DOS SANTOS, MARCO CESAR GOLDBARG, and ELIZABETH F. GOUVEA GOLDBARG. "UMA ANÁLISE SOBRE O PROBLEMA DO CAIXEIRO VIAJANTE ELÉTRICO COM PASSAGEIROS." In Brazilian Congress. brazco, 2020. http://dx.doi.org/10.51162/brc.dev2020-00072.

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Neste artigo apresentamos uma analise sobre o Problema do Caixeiro Viajante Eletrico com Passageiros - PCVEP. O problema e uma variante do classico Problema do Caixeiro Viajante (PCV), que considera elementos de compartilhamento solidario de assentos em veiculos, alem do advento do veiculo utilizado pelo caixeiro ser unicamente eletrico, sendo ambas as questoes atuais, importantes e bastante discutidas nas areas de pesquisa operacional e otimizacao combinatoria. No PCVEP, alem de se determinar a menor rota mediante um conjunto de cidades como no PCV, os custos de deslocamento do motorista sao
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Yokoyama, Soichiro, Ikuo Suzuki, Masahito Yamamoto, and Masashi Furukawa. "A New Heuristic for Traveling Salesman Problem Based on LCO." In ASME/ISCIE 2012 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/isfa2012-7227.

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The Traveling Salesman Problem (TSP) is one of the most well known combinatorial optimization problem and has wide range of application. Since the TSP is NP-hard, many heuristics for the TSP have been developed. This study proposes a new heuristic for the TSP based on one of these heuristics named Local Clustering Optimization (LCO). LCO is a metaheuristic proposed by Furukawa at el. to give an accurate solution for large scale problems in a reasonable time. However, conventional LCO-based heuristics for the TSP is not suited to solving asymmetric instances. The proposed method iteratively ado
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Gao, Chengrui, Haopu Shang, Ke Xue, Dong Li, and Chao Qian. "Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/764.

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Machine learning has been adapted to help solve NP-hard combinatorial optimization problems. One prevalent way is learning to construct solutions by deep neural networks, which has been receiving more and more attention due to the high efficiency and less requirement for expert knowledge. However, many neural construction methods for Vehicle Routing Problems~(VRPs) focus on synthetic problem instances with specified node distributions and limited scales, leading to poor performance on real-world problems which usually involve complex and unknown node distributions together with large scales. T
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Nie, Xiaonan, Xupeng Miao, Zhi Yang, and Bin Cui. "TSPLIT: Fine-grained GPU Memory Management for Efficient DNN Training via Tensor Splitting." In 2022 IEEE 38th International Conference on Data Engineering (ICDE). IEEE, 2022. http://dx.doi.org/10.1109/icde53745.2022.00241.

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Liao, Jing, Yadong Wu, Guijuan Wang, Fupan Wang, Huarong Chen, and Li Long. "TSPvis: A Temperature Sensitive Paint Formulation Visual Design System." In 2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI). IEEE, 2023. http://dx.doi.org/10.1109/prai59366.2023.10331982.

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Reports on the topic "TSPLIB"

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Williams, Tommy Jay. Tonopah Test Range Optical Tracking TSPI Uncertainty Qualification Analysis. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1459100.

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Lai, Ying-Cheng. Time-Frequency Filtering and Carrier-Phase Ambiguity Resolution for GPS-Based TSPI Systems in Jamming Environment. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada476563.

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