Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
119 tokens/sec
GPT-4o
56 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A Systematic Review of Approximability Results for Traveling Salesman Problems leveraging the TSP-T3CO Definition Scheme (2311.00604v2)

Published 1 Nov 2023 in cs.DS

Abstract: The traveling salesman (or salesperson) problem, short TSP, is a problem of strong interest to many researchers from mathematics, economics, and computer science. Manifold TSP variants occur in nearly every scientific field and application domain: engineering, physics, biology, life sciences, and manufacturing just to name a few. Several thousand papers are published on theoretical research or application-oriented results each year. This paper provides the first systematic survey on the best currently known approximability and inapproximability results for well-known TSP variants such as the "standard" TSP, Path TSP, Bottleneck TSP, Maximum Scatter TSP, Generalized TSP, Clustered TSP, Traveling Purchaser Problem, Profitable Tour Problem, Quota TSP, Prize-Collecting TSP, Orienteering Problem, Time-dependent TSP, TSP with Time Windows, and the Orienteering Problem with Time Windows. The foundation of our survey is the definition scheme T3CO, which we propose as a uniform, easy-to-use and extensible means for the formal and precise definition of TSP variants. Applying T3CO to formally define the variant studied by a paper reveals subtle differences within the same named variant and also brings out the differences between the variants more clearly. We achieve the first comprehensive, concise, and compact representation of approximability results by using T3CO definitions. This makes it easier to understand the approximability landscape and the assumptions under which certain results hold. Open gaps become more evident and results can be compared more easily.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (212)
  1. Improving Christofides' algorithm for the s-t Path TSP. Journal of the ACM, 62(5):1–28, 2015.
  2. Approximation algorithms for the bottleneck asymmetric traveling salesman problem. ACM Transactions on Algorithms, 17(4):1–12, 2021.
  3. A 5/3-approximation algorithm for the clustered traveling salesman tour and path problems. Operations Research Letters, 24(1-2):29–35, 1999.
  4. The traveling salesman problem. Princeton University Press, 2011.
  5. Improved approximation algorithms for prize-collecting Steiner tree and TSP. SIAM Journal on Computing, 40(2):309–332, 2011.
  6. On the maximum scatter traveling salesperson problem. SIAM Journal of Computing, 29(2):515––544, 1999.
  7. Resource-constrained geometric network optimization. In Proc. 14th Annual Symposium on Computational Geometry, pages 307–316. ACM, 1998.
  8. Sanjeev Arora. Polynomial time approximation schemes for Euclidean TSP and other geometric problems. In Proc. 37th Conference on Foundations of Computer Science, pages 2–11. IEEE, 1996.
  9. Solving the asymmetric travelling salesman problem with time windows by branch-and-cut. Mathematical Programming, 90(3):475–506, 2001.
  10. Linear time approximation schemes for vehicle scheduling problems. Theoretical Computer Science, 324(2-3):147–160, 2004.
  11. Prize collecting traveling salesman and related problems. In Teofilo F. Gonzalez, editor, Handbook of Approximation Algorithms and Metaheuristics, Volume 1: Methologies and Traditional Applications, pages 611–628. Chapman and Hall/CRC, 2018.
  12. New approximation guarantees for minimum-weight k-trees and prize-collecting salesmen. SIAM Journal on Computing, 28(1):254–262, 1998.
  13. An Introduction to Description Logic. Cambridge University Press, 2017.
  14. The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, 2007.
  15. Complexity results for SAS+ planning. Computational Intelligence, 11(4):625–655, 1995.
  16. Principes of Sequencing and Scheduling. Wiley, 1974.
  17. The sequencing problem. Management Science, 16(4):B.247–B.263, 1969.
  18. Egon Balas. The prize collecting traveling salesman problem. Networks, 19(6):621–636, 1989.
  19. The precedence-constrained asymmetric traveling salesman polytope. Mathematical Programming, 68(1):241–265, 1995.
  20. Approximation algorithms for deadline-tsp and vehicle routing with time-windows. In Proc. 36th Annual ACM symposium on Theory of computing, pages 166–174. ACM, 2004.
  21. A note on approximation algorithms of the clustered traveling salesman problem. Information Processing Letters, 127:54–57, 2017.
  22. On approximating a geometric prize-collecting traveling salesman problem with time windows. Journal of Algorithms, 55(1):76–92, 2005.
  23. Prize-collecting Steiner Problems on Planar Graphs, pages 1028––1049. ACM, 2011.
  24. The traveling purchaser problem, with multiple stacks and deliveries: A branch-and-cut approach. Computers & operations research, 40(8):2103–2115, 2013.
  25. Transformation of multisalesman problem to the standard traveling salesman problem. Journal of the ACM, 21(3):500–504, 1974.
  26. A 3/2-approximation for the Metric Many-Visits Path TSP. SIAM Journal on Discrete Mathematics, 36(4):2995–3030, 2022.
  27. Approximation algorithms for geometric problems. In Dorit S. Hochbaum, editor, Approximation Algorithms for NP-hard Problems, pages 296–345. PWS Publishing Co., 1996.
  28. The Semantic Web. Scientific American, 284(5):34–43, 2001.
  29. A branch-and-cut algorithm for the undirected prize collecting traveling salesman problem. Networks: An Int. Journal, 54(1):56–67, 2009.
  30. Approximation algorithms for generalized MST and TSP in grid clusters. In Proc. 9th Int. Conf. on Combinatorial Optimization and Applications, pages 110–125. Springer, 2015.
  31. A note on the prize collecting traveling salesman problem. Mathematical programming, 59(1):413–420, 1993.
  32. The time-dependent traveling salesman problem and single machine scheduling problems with sequence dependent setup times. Discrete Optimization, 5(4):685–699, 2008.
  33. An improved approximation guarantee for prize-collecting tsp. In Proc. 55th Annual ACM Symposium on Theory of Computing, pages 1848––1861. ACM, 2023.
  34. Handbook on scheduling: From theory to practice. Springer, 2019.
  35. Approximation algorithms for orienteering and discounted-reward TSP. SIAM Journal on Computing, 37(2):653–670, 2007.
  36. The parameterized approximability of TSP with deadlines. Theory of Computing Systems, 41(3):431–444, 2007.
  37. Approximation hardness of deadline-tsp reoptimization. Theoretical Computer Science, 410(21-23):2241–2249, 2009.
  38. Lawrence D Bodin. A taxonomic structure for vehicle routing and scheduling problems. Computers and Urban Society, 1:11––29, 1975.
  39. Classification in vehicle routing and scheduling. Networks, 11:97––108, 1981.
  40. Ant colony optimization for the traveling purchaser problem. Computers & Operations Research, 35(2):628–637, 2008.
  41. The vehicle routing problem: State of the art classification and review. Computers & Industrial Engineering, 99:300–313, 2016.
  42. Online and offline algorithms for the time-dependent TSP with time zones. Algorithmica, 39(4):299–319, 2004.
  43. Peter Brucker. Scheduling Algorithms. Springer, 1995.
  44. Well-solvable special cases of the traveling salesman problem: A survey. SIAM Review, 40(3):496–546, 1998.
  45. Rodney Matineau Burstall. A heuristic method for a job-scheduling problem. Journal of the Operational Research Society, 17:291–304, 1966.
  46. Tom Bylander. Complexity results for planning. In Proc. 12th Int. Joint Conference on Artificial Intelligence, volume 10, pages 274–279, 1991.
  47. Single-vehicle scheduling problem on a straight line with time window constraints. In Proc. 1st Int. Computing and Combinatorics Conference, pages 617–626. Springer, 1995.
  48. A comprehensive survey on the multiple traveling salesman problem: Applications, approaches and taxonomy. Computer Science Review, 40:100369, 2021.
  49. Improved algorithms for orienteering and related problems. ACM Transactions on Algorithms, 8(3):1–27, 2012.
  50. Maximum coverage problem with group budget constraints and applications. In Approximation, Randomization, and Combinatorial Optimization - Algorithms and Techniques, pages 72–83. Springer, 2004.
  51. A recursive greedy algorithm for walks in directed graphs. In 46th Annual IEEE Symposium on Foundations of Computer Science, pages 245–253. IEEE, 2005.
  52. Ke Chen and Sariel Har-Peled. The Euclidean orienteering problem revisited. SIAM Journal on Computing, 38(1):385–397, 2008.
  53. Yongyu Chen. Approximation schemes for capacity vehicle routing problems: A survey. arXiv preprint arXiv:2306.01826, 2023.
  54. Yi-Jen Chiang. New approximation results for the maximum scatter TSP. Algorithmica, 41(4):309–341, 2005.
  55. State-space relaxation procedures for the computation of bounds to routing problems. Networks, 11(2):145–164, 1981.
  56. Edward G Coffman. Computer and Job-Shop Scheduling Theory. Wiley, 1976.
  57. Theory of scheduling. Addison Wesley, 1967.
  58. Multiobjective transportation network design and routing problems: Taxonomy and annotation. European Journal of Operational Research, 65(1):4–19, 1993.
  59. Multiobjective design of transportation networks: Taxonomy and annotation. European Journal of Operational Research, 26(2):187–201, 1986.
  60. Solution of a large-scale traveling-salesman problem. Journal of the Operations Research Society of America, 2(4):393–410, 1954.
  61. The truck dispatching problem. Management Science, 6(1):80–91, 1959.
  62. Sequencing and scheduling in robotic cells: Recent developments. Journal of Scheduling, 8(5):387–426, 2005.
  63. H. N. de Ridder et al. Information System on Graph Classes and their Inclusions (ISGCI). https://www.graphclasses.org.
  64. Four-point conditions for the TSP: The complete complexity classification. Discrete optimization, 14:147–159, 2014.
  65. On prize-collecting tours and the asymmetric travelling salesman problem. Int. Transactions in Operational Research, 2(3):297–308, 1995.
  66. Modeling and Optimization in Green Logistics. Springer, 2020.
  67. A new optimization algorithm for the vehicle routing problem with time windows. Operations Research, 40(2):342–354, 1992.
  68. Towards a model and algorithm management system for vehicle routing and scheduling problems. Decision support systems, 25(2):109–133, 1999.
  69. Vehicle routing with time windows: optimization and approximation. In B. L. Golden and A.A. Assad, editors, Vehicle Routing: Methods and Studies. Elsevier, 1988.
  70. A classification scheme for vehicle routing and scheduling problems. European Journal of Operational Research, 46(3):322–332, 1990.
  71. Two-level genetic algorithm for clustered traveling salesman problem with application in large-scale TSPs. Tsinghua Science & Technology, 12(4):459–465, 2007.
  72. Lincoln P. Djang. The wandering salesman problem. PhD thesis, The University of Texas at Arlington, 1993.
  73. Approximation algorithms for TSP with neighborhoods in the plane. Journal of Algorithms, 48(1):135–159, 2003.
  74. The vehicle routing problem: A taxonomic review. Computers and Industrial Engineering, 57:1472––1483, 2009.
  75. A tight bound on approximating arbitrary metrics by tree metrics. In Proc. 35th Annual ACM Symposium on Theory of Computing, pages 448–455, 2003.
  76. Deadline TSP. Theoretical Computer Science, 771:83–92, 2019.
  77. Improved approximation ratios for traveling salesperson tours and paths in directed graphs. In Int. Workshop on Approximation Algorithms for Combinatorial Optimization, pages 104–118. Springer, 2007.
  78. Traveling salesman problems with profits. Transportation Science, 39(2):188–205, 2005.
  79. The symmetric quadratic traveling salesman problem. Mathematical Programming, 142(1):205–254, 2013.
  80. A branch-and-cut algorithm for the symmetric generalized traveling salesman problem. Operations Research, 45(3):378–394, 1997.
  81. Approximation algorithms for time-dependent orienteering. Information Processing Letters, 83(2):57–62, 2002.
  82. PDDL2. 1–An extension to PDDL for expressing temporal planning domains. Journal of Artificial Intelligence Research, 20:61–124, 2003.
  83. Approximation algorithms for the traveling repairman and speeding deliveryman problems. Algorithmica, 62(3):1198–1221, 2012.
  84. Compact, provably-good LPs for orienteering and regret-bounded vehicle routing. In Proc. 19th Int. Conference on Integer Programming and Combinatorial Optimization, pages 199–211. Springer, 2017.
  85. Constant-factor approximation to deadline TSP and related problems in (almost) quasi-polytime. In 48th Int. Colloquium on Automata, Languages, and Programming. Schloss Dagstuhl-Leibniz-Zentrum für Informatik, 2021.
  86. Approximation algorithms for time-window TSP and prize collecting TSP problems. In Algorithmic Foundations of Robotics XII, pages 560–575. Springer, 2020.
  87. The bottleneck traveling salesman problem: Algorithms and probabilistic analysis. Journal of the ACM (JACM), 25(3):435–448, 1978.
  88. Naveen Garg. Saving an epsilon: a 2-approximation for the k-MST problem in graphs. In Proc. of the 37th Annual ACM symposium on Theory of Computing, pages 396–402, 2005.
  89. A polylogarithmic approximation algorithm for the group Steiner tree problem. Journal of Algorithms, 37(1):66–84, 2000.
  90. Time-dependent routing problems: A review. Computers & operations research, 64:189–197, 2015.
  91. A generalized insertion heuristic for the traveling salesman problem with time windows. Operations Research, 46(3):330–335, 1998.
  92. Aleksey N. Glebov. A 5/6-approximation algorithm for the pseudo-metric TSP-max in an incomplete graph. In Proc. 17th Int. Baikal Seminar on Optimization Methods and Applications, 2017.
  93. A general approximation technique for constrained forest problems. SIAM Journal on Computing, 24(2):296–317, 1995.
  94. The orienteering problem. Naval Research Logistics, 34(3):307–318, 1987.
  95. The vehicle routing problem: latest advances and new challenges, volume 43. Springer, 2008.
  96. A classification of formulations for the (time-dependent) traveling salesman problem. European Journal of Operational Research, 83(1):69–82, 1995.
  97. Optimization and approximation in deterministic sequencing and scheduling: a survey. In Annals of Discrete Mathematics, volume 5, pages 287–326. Elsevier, 1979.
  98. Approximation algorithms for connected dominating sets. Algorithmica, 20(4):374–387, 1998.
  99. The online food delivery problem on stars. Theoretical Computer Science, 928:13–26, 2022.
  100. The traveling salesman problem and its variations, volume 12. Springer, 2006.
  101. Approximation algorithms for not necessarily disjoint clustered tsp. Journal of Graph Algorithms and Applications, 22(4):555–575, 2018.
  102. Bounds and heuristics for capacitated routing problems. Mathematics of Operations Research, 10(4):527–542, 1985.
  103. Approximation results for kinetic variants of TSP. Discrete & Computational Geometry, 27:635–651, 2002.
  104. Dynamic shortest paths methods for the time-dependent TSP. Algorithms, 14(1):21–44, 2021.
  105. Moving-target TSP and related problems. In European Symposium on Algorithms, pages 453–464. Springer, 1998.
  106. The moving-target traveling salesman problem. Journal of Algorithms, 49(1):153–174, 2003.
  107. The maximum scatter TSP on a regular grid. In Selected Papers of the Int. Conference of the German, Austrian and Swiss Operations Research Societies, pages 63–70. Springer, 2017.
  108. Chapter 1: The family of vehicle routing problems. In Vehicle Routing: Problems, Methods, and Applications, pages 1–33. SIAM, 2014.
  109. An approximation algorithm for a bottleneck traveling salesman problem. Journal of Discrete Algorithms, 7(3):315–326, 2009.
  110. New formulations for the orienteering problem. Procedia Economics and Finance, 39:849–854, 2016.
  111. A (slightly) improved approximation algorithm for metric TSP. In Proc. 53rd Annual ACM SIGACT Symposium on Theory of Computing, pages 32–45, 2021.
  112. Richard M. Karp. Reducibility among combinatorial problems. In Raymond E. Miller, James W. Thatcher, and Jean D. Bohlinger, editors, Proc. Symposium on the Complexity of Computer Computations, pages 85–103. Springer, 1972.
  113. New inapproximability bounds for TSP. Journal of Computer and System Sciences, 81(8):1665––1677, 2015.
  114. Vehicle scheduling on a tree with release and handling times. Annals of Operations Research, 69:193–207, 1997.
  115. A 1.5-approximation for single-vehicle scheduling problem on a line with release and handling times. In Japan-USA Symposium on Flexible Automation, pages 1363–1366. ISCIE/ASME, 1998.
  116. Better approximation ratios for the single-vehicle scheduling problems on line-shaped networks. Networks, 39(4):203–209, 2002.
  117. An algorithm for single constraint maximum collection problem. Journal of the Operations Research Society of Japan, 31(4):515–531, 1988.
  118. Improving approximation rations for the clustered traveling salesman problem. Journal of the Operations Research Society of Japan, 63(2):60–70, 2020.
  119. PTAS for the euclidean capacitated vehicle routing problem. In Proc. 9th Int. Conference on Discrete Optimization and Operations Research, pages 193–205. Springer, 2016.
  120. Constant-factor approximation algorithms for a series of combinatorial routing problems based on the reduction to the asymmetric traveling salesman problem. Proc. of the Steklov Institute of Mathematics, 319(Suppl 1):S140–S155, 2022.
  121. Complexity and approximability of the euclidean generalized traveling salesman problem in grid clusters. Annals of Mathematics and Artificial Intelligence, 88(1):53–69, 2020.
  122. Improved polynomial time approximation scheme for capacitated vehicle routing problem with time windows. In Proc. 4th Int. Conference on Optimization and Applications, pages 155–169. Springer, 2018.
  123. Approximation scheme for the capacitated vehicle routing problem with time windows and non-uniform demand. In Proc. 18th Int. Conference on Mathematical Optimization Theory and Operations Research, pages 309–327. Springer, 2019.
  124. Philip N. Klein. A linear-time approximation scheme for planar weighted TSP. In 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05), pages 647–656, 2005.
  125. Philip N. Klein. A subset spanner for planar graphs, with application to subset tsp. In Proceedings of the Thirty-Eighth Annual ACM Symposium on Theory of Computing, STOC '06, page 749–756, New York, NY, USA, 2006. Association for Computing Machinery.
  126. Cable tree wiring-benchmarking solvers on a real-world scheduling problem with a variety of precedence constraints. Constraints, pages 1–51, 2021.
  127. The asymmetric traveling salesman path LP has constant integrality ratio. Mathematical Programming, 183(1-2):379–395, 2020.
  128. A survey of approximate methods for the traveling salesman problem. Kasetsart Engineering Journal, 27(89):79–87, 2014.
  129. Nitish J. Korula. Approximation algorithms for network design and orienteering. University of Illinois at Urbana-Champaign, 2010.
  130. A PTAS for euclidean maximum scatter TSP. In Proc. 32nd European Workshop on Computational Geometry, page abs/1512.02963. CoRR, 2015.
  131. Rich vehicle routing problems: From a taxonomy to a definition. European Journal of Operational Research, 241(1):1–14, 2015.
  132. Classification of travelling salesman problem formulations. Operations Research Letters, 9(2):127–132, 1990.
  133. Gilbert Laporte. The traveling salesman problem: An overview of exact and approximate algorithms. European Journal of Operational Research, 59(2):231–247, 1992.
  134. The selective travelling salesman problem. Discrete Applied Mathematics, 26(2-3):193–207, 1990.
  135. Routing problems: A bibliography. Annals of operations research, 61(1):227–262, 1995.
  136. Some applications of the clustered travelling salesman problem. Journal of the Operational Research Society, 53(9):972–976, 2002.
  137. A tabu search heuristic using genetic diversification for the clustered traveling salesman problem. Journal of Heuristics, 2(3):187–200, 1997.
  138. A branch-and-cut algorithm for the undirected traveling purchaser problem. Operations Research, 51(6):940–951, 2003.
  139. The asymmetric bottleneck traveling salesman problem: algorithms, complexity and empirical analysis. Computers & Operations Research, 43:20–35, 2014.
  140. Sequencing and scheduling: Algorithms and complexity. Handbooks in Operations Research and Management Science, 4:445–522, 1993.
  141. A taxonomy of constraints in simulation-based optimization. arXiv preprint arXiv:1505.07881, 2015.
  142. Strong linear programming relaxations for the orienteering problem. European Journal of Operational Research, 73(3):517–523, 1994.
  143. Transformation of the generalized traveling-salesman problem into the standard traveling-salesman problem. Information Sciences, 74(1-2):177–189, 1993.
  144. Survey of green vehicle routing problem: past and future trends. Expert Systems with Applications, 41(4):1118–1138, 2014.
  145. A restricted dynamic programming heuristic algorithm for the time dependent traveling salesman problem. European Journal of Operational Research, 90(1):45–55, 1996.
  146. The traveling purchaser problem and its variants. European Journal of Operational Research, 259(1):1–18, 2017.
  147. Quota traveling salesman with passengers and collection time. In 28th Brazilian Conference on Intelligent Systems, pages 299–304. IEEE, 2019.
  148. Multidisciplinary design optimization: a survey of architectures. AIAA journal, 51(9):2049–2075, 2013.
  149. Drew M. McDermott. The 1998 ai planning systems competition. AI Magazine, 21(2):35––55, 2000.
  150. Drew M McDermott. PDDL2. 1–The art of the possible? Commentary on Fox and Long. Journal of Artificial Intelligence Research, 20:145–148, 2003.
  151. Karl Menger. Das Botenproblem. Ergebnisse eines mathematischen Kolloquiums, 2(4):11–12, 1932.
  152. Integer programming formulation of traveling salesman problems. Journal of the ACM, 7(4):326–329, 1960.
  153. Combined location-routing problems: A synthesis and future research directions. European Journal of Operational Research, 108(1):1–15, 1998.
  154. Joseph S. B. Mitchell. Guillotine subdivisions approximate polygonal subdivisions: A simple polynomial-time approximation scheme for geometric TSP, k-MST, and related problems. SIAM Journal on Computing, 28(4):1298–1309, 1999.
  155. Approximating graphic TSP by matchings. In 52nd Annual IEEE Symposium on Foundations of Computer Science, pages 560–569. IEEE, 2011.
  156. Removing and adding edges for the traveling salesman problem. Journal of the ACM, 63(1):1–28, 2016.
  157. A literature review on the vehicle routing problem with multiple depots. Computers & Industrial Engineering, 79:115–129, 2015.
  158. Marcin Mucha. -approximation for graphic TSP. Theory of Computing Systems, 55(4):640–657, 2014.
  159. Complexity of the single vehicle scheduling problem on graphs. Information Systems and Operational Research, 35(4):256–276, 1997.
  160. The directed orienteering problem. Algorithmica, 60(4):1017–1030, 2011.
  161. Reasoning about temporal relations: A maximal tractable subclass of Allen's interval algebra. Journal of the ACM, 42(1):43–66, 1995.
  162. Approximating the asymmetric profitable tour. Int. Journal of Mathematics in Operational Research, 4(3):294–301, 2012.
  163. Charles E. Noon. The generalized traveling salesman problem. PhD thesis, University of Michigan, 1988.
  164. An efficient transformation of the generalized traveling salesman problem. Information Systems and Operational Research, 31(1):39–44, 1993.
  165. Web Ontology Language (OWL), 2012.
  166. A comprehensive review and evaluation of permutation flowshop heuristics to minimize flowtime. Computers & Operations Research, 40(1):117–128, 2013.
  167. On two geometric problems related to the travelling salesman problem. Journal of Algorithms, 5(2):231–246, 1984.
  168. On the approximability of the traveling salesman problem. Combinatorica, 26(1):101–120, 2006.
  169. Guaranteed performance heuristics for the bottleneck travelling salesman problem. Operations Research Letters, 2(6):269––272, 1984.
  170. Richard E. Pattis. Teaching EBNF first in CS 1. ACM SIGCSE Bulletin, 26(1):300–303, 1994.
  171. Prize-collecting TSP with a budget constraint. In 25th Annual European Symposium on Algorithms. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2017.
  172. Budgeted prize-collecting traveling salesman and minimum spanning tree problems. Mathematics of Operations Research, 45(2):576–590, 2020.
  173. A survey of algorithms for single and multi-objective unrelated parallel-machine deterministic scheduling problems. Journal of the Chinese Institute of Industrial Engineers, 21(3):230–241, 2004.
  174. The time-dependent traveling salesman problem and its application to the tardiness problem in one-machine scheduling. Operations research, 26(1):86–110, 1978.
  175. A review of dynamic vehicle routing problems. European Journal of Operational Research, 225(1):1–11, 2013.
  176. Michael Pinedo. Scheduling. Springer, 4 edition, 2012.
  177. Michael Pinedo. Scheduling. Springer, 6 edition, 2016.
  178. A comprehensive survey on the generalized traveling salesman problem. European Journal of Operational Research, 2023.
  179. A representational paradigm for dynamic resource transformation problems. Annals of Operations Research, 104(1-4):231–279, 2001.
  180. Harilaos N. Psaraftis. Dynamic vehicle routing: Status and prospects. Annals of Operations Research, 61(1):143–164, 1995.
  181. Routing and scheduling on a shoreline with release times. Management Science, 36(2):212–223, 1990.
  182. Dynamic vehicle routing problems: Three decades and counting. Networks, 67(1):3–31, 2016.
  183. M. R. Rao. A note on the multiple traveling salesmen problem. Operations Research, 28(3):628–632, 1980.
  184. Approximation algorithms for the traveling purchaser problem and its variants in network design. In European Symposium on Algorithms, pages 29–40. Springer, 1999.
  185. Gerhard Reinelt. TSPLIB — A traveling salesman problem library. ORSA Journal on Computing, 3(4):376–384, 1991.
  186. On the complexity of qualitative spatial reasoning: A maximal tractable fragment of the region connection calculus. Artificial Intelligence, 108(1-2):69–123, 1999.
  187. Michael Rothkopf. The traveling salesman problem: On the reduction of certain large problems to smaller ones. Operations Research, 14(3):532–533, 1966.
  188. A comprehensive review and evaluation of permutation flowshop heuristics. European Journal of Operational Research, 165(2):479–494, 2005.
  189. Martin W. Savelsbergh. Local search in routing problems with time windows. Annals of Operations Research, 4(1):285–305, 1985.
  190. A discrete firefly meta-heuristic with local search for makespan minimization in permutation flow shop scheduling problems. Int. Journal of Industrial Engineering Computations, 1(1):1–10, 2010.
  191. Alexander Schrijver. Combinatorial Optimization: Polyhedra and Efficiency. Springer, 2003.
  192. András Sebő. Eight-fifth approximation for the path TSP. In Proc. 16th Int. Conference on Integer Programming and Combinatorial Optimization, pages 362–374. Springer, 2013.
  193. The salesman's improved paths: A 3/2+ 1/34 approximation. In 57th Annual IEEE Symposium on Foundations of Computer Science, pages 118–127. IEEE, 2016.
  194. Shorter tours by nicer ears: 7/5-approximation for the graph-TSP, 3/2 for the path version, and 4/3 for two-edge-connected subgraphs. Combinatorica, pages 1–34, 2014.
  195. A random-key genetic algorithm for the generalized traveling salesman problem. European Journal of Operational Research, 174(1):38–53, 2006.
  196. Marius M. Solomon. Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research, 35(2):254–265, 1987.
  197. A constant-factor approximation algorithm for the asymmetric traveling salesman problem. Journal of the ACM, 67(6):1–53, 2020.
  198. Maciej M. Sysło. Generalizations of the standard travelling salesman problem. Applicationes Mathematicae, 4(16):621–629, 1980.
  199. A classification of methods for distributed system optimization based on formulation structure. Structural and Multidisciplinary Optimization, 39(5):503–517, 2009.
  200. The vehicle routing problem. SIAM, 2002.
  201. Vehicle routing: problems, methods, and applications. SIAM, 2 edition, 2014.
  202. Vera Traub. Approximation Algorithms for Traveling Salesman Problems. PhD thesis, Rheinische Friedrich-Wilhelms-Universität Bonn, 2020.
  203. Beating the integrality ratio for s-t-tours in graphs. SIAM Journal on Computing, 2020. Special Section FOCS 2018.
  204. An improved approximation algorithm for ATSP. In Proc. 52nd Annual ACM SIGACT Symposium on Theory of Computing, pages 1––13. ACM, 2020.
  205. Reducing Path TSP to TSP. In Proc. 52nd Annual ACM SIGACT Symposium on Theory of Computing, pages 14––27. ACM, 2020.
  206. Theodore Tsiligirides. Heuristic methods applied to orienteering. Journal of the Operational Research Society, 35(9):797–809, 1984.
  207. John N Tsitsiklis. Special cases of traveling salesman and repairman problems with time windows. Networks, 22(3):263–282, 1992.
  208. The orienteering problem: a survey. European Journal of Operational Research, 209(1):1–10, 2011.
  209. Jens Vygen. New approximation algorithms for the TSP, 2012.
  210. Parameterized algorithms and complexity for the traveling purchaser problem and its variants. Journal of Combinatorial Optimization, pages 1–17, 2020.
  211. Single-vehicle scheduling with time window constraints. Journal of Scheduling, 2(4):175–187, 1999.
  212. Rico Zenklusen. A 1.5-approximation for path TSP. In Proc. 13th Annual ACM-SIAM symposium on discrete algorithms, pages 1539–1549. SIAM, 2019.
User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (3)
  1. Sophia Saller (5 papers)
  2. Jana Koehler (4 papers)
  3. Andreas Karrenbauer (19 papers)
Citations (3)

Summary

We haven't generated a summary for this paper yet.