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Well-Solvable Special Cases of the Traveling Salesman Problem: A Survey

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Gerhard J. WoegingerAuthors Info & Claims

SIAM Review, Volume 40, Issue 3

Pages 496 - 546

https://doi.org/10.1137/S0036144596297514

Published: 01 September 1998 Publication History

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Abstract

The traveling salesman problem (TSP) belongs to the most basic, most important, and most investigated problems in combinatorial optimization. Although it is an ${\cal NP}$-hard problem, many of its special cases can be solved efficiently in polynomial time. We survey these special cases with emphasis on the results that have been obtained during the decade 1985--1995. This survey complements an earlier survey from 1985 compiled by Gilmore, Lawler, and Shmoys [The Traveling Salesman Problem---A Guided Tour of Combinatorial Optimization, Wiley, Chichester, pp. 87--143].

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Kim YAmano MYamamoto D(2023)A 1.5-Approximation Route Finding for a Ride-sharing considering Movement of PassengersProceedings of the 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility10.1145/3615899.3627933(59-69)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3615899.3627933
Khatami MSalehipour ACheng T(2023)Flow-shop scheduling with exact delays to minimize makespanComputers and Industrial Engineering10.1016/j.cie.2023.109456183:COnline publication date: 17-Oct-2023
https://dl.acm.org/doi/10.1016/j.cie.2023.109456
Strusevich V(2022)Complexity and approximation of open shop scheduling to minimize the makespanComputers and Operations Research10.1016/j.cor.2022.105732144:COnline publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1016/j.cor.2022.105732
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Index Terms

Well-Solvable Special Cases of the Traveling Salesman Problem: A Survey
1. Mathematics of computing
  1. Mathematical analysis
    1. Mathematical optimization
2. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization
  2. Models of computation
    1. Abstract machines

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Society for Industrial and Applied Mathematics

United States

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Published: 01 September 1998

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Kim YAmano MYamamoto D(2023)A 1.5-Approximation Route Finding for a Ride-sharing considering Movement of PassengersProceedings of the 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility10.1145/3615899.3627933(59-69)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3615899.3627933
Khatami MSalehipour ACheng T(2023)Flow-shop scheduling with exact delays to minimize makespanComputers and Industrial Engineering10.1016/j.cie.2023.109456183:COnline publication date: 17-Oct-2023
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Strusevich V(2022)Complexity and approximation of open shop scheduling to minimize the makespanComputers and Operations Research10.1016/j.cor.2022.105732144:COnline publication date: 1-Aug-2022
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Su YLi MZhu XLi C(2022)Steiner TSP based on aisle as a unit for order pickingComputers and Industrial Engineering10.1016/j.cie.2022.108026168:COnline publication date: 1-Jun-2022
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Lenstra JRendl FSpieksma FUetz M(2022)In memoriam Gerhard WoegingerJournal of Scheduling10.1007/s10951-022-00748-425:5(503-505)Online publication date: 1-Oct-2022
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Berg MBuchin KJansen BWoeginger G(2020)Fine-grained Complexity Analysis of Two Classic TSP VariantsACM Transactions on Algorithms10.1145/341484517:1(1-29)Online publication date: 31-Dec-2020
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Füßler DFedtke SBoysen N(2019)The cafeteria problem: order sequencing and picker routing in on-the-line picking systemsOR Spectrum10.1007/s00291-019-00553-041:3(727-756)Online publication date: 1-Sep-2019
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Jiaoman DLei LXiang LHung CSaid L(2018)Travel planning problem considering site selection and itinerary makingProceedings of the 2018 Conference on Research in Adaptive and Convergent Systems10.1145/3264746.3264781(29-36)Online publication date: 9-Oct-2018
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