Skip to content
DraconiticResearch
Search Sources API
178,970 studies31 sourcesUpdated 42 min ago
PreprintCC BY-SA 4.0arXiv

Closing All-Exp Gaps in Local Search for the Traveling Salesman Problem and Maximum Constraint Assignment

Abstract

We prove the all-exp property for the Traveling Salesman Problem with the $2$-opt neighborhood, and for (3,2,2)- and (2,3,2)-Maximum Constraint Assignment with the flip neighborhood. The all-exp property states that infinitely many instances have an initial solution from which every sequence of improving moves to a local optimum, and hence every run of local search, has exponential length. For the Traveling Salesman Problem, the all-exp property was previously known for every k-opt neighborhood with k ≥ 3, so our result for $2$-opt completes the picture for all k-kopt neighborhoods. In (p,q,r)-Maximum Constraint Assignment, each constraint involves at most p variables, each variable occurs in at most q constraints, and each domain has size r. Decreasing any of the parameters of (3,2,2) or (2,3,2) yields a problem in which every sequence of improving flips has polynomial length, so both Maximum Constraint Assignment results are tight. All three results settle long-standing open problems. Our proofs build on a common construction idea, which reveals a close connection between the local-search dynamics of the three problems.

Related

  1. Exact cost of the Euclidean Maximum Traveling Salesman Problem in one dimension
    Sergio Caracciolo, Carlo Vanoni
    arXivPreprintarXiv licenceFull textCombinatorics & discrete mathematicsMathematical physicsarXiv
  2. Traveling Salesman Problem on Graphs with Proportional Independent Set
    Ethan X. Fang, Shengtao Guo, Junwei Lu +1
    arXivPreprintCC BY 4.0Full textCombinatorics & discrete mathematicsarXiv
  3. On the Segment-Based Remove-and-Reinsert Heuristic for the Generalized Traveling Salesman Problem
    Aljaž Krpan, Janez Žerovnik
    MathematicsPeer-reviewedCC BY 4.0General mathematicsCrossref
  4. Collaborative Attention Ant Colony Optimization for Large-Scale Traveling Salesman Problems
    Kexin Zhang, Shubin Liu, Xinyuan Zhang +1
    MathematicsPeer-reviewedCC BY 4.0General mathematicsCrossref
  5. Optimal Service Commitments in Traveling Salesman Problems with Stochastic Demand
    Lina Schmidt, Julian Golak, Arne Schulz +1
    arXivPreprintCC BY 4.0Full textOptimisation & controlarXiv
BibTeX
@misc{heimann2026closing,
  title = {{Closing All-Exp Gaps in Local Search for the Traveling Salesman Problem and Maximum Constraint Assignment}},
  author = {Sophia Heimann and Hung P. Hoang and Stefan Hougardy},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.31513},
  eprint = {2610.31513},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.31513},
  note = {CC BY-SA 4.0},
}
RIS
TY  - UNPB
TI  - Closing All-Exp Gaps in Local Search for the Traveling Salesman Problem and Maximum Constraint Assignment
AU  - Sophia Heimann
AU  - Hung P. Hoang
AU  - Stefan Hougardy
PY  - 2026
DA  - 2026/10/22
PB  - arXiv
DO  - 10.48550/arxiv.2610.31513
UR  - https://arxiv.org/abs/2610.31513
AB  - We prove the all-exp property for the Traveling Salesman Problem with the $2$-opt neighborhood, and for (3,2,2)- and (2,3,2)-Maximum Constraint Assignment with the flip neighborhood. The all-exp property states that infinitely many instances have an initial solution from which every sequence of improving moves to a local optimum, and hence every run of local search, has exponential length. For the Traveling Salesman Problem, the all-exp property was previously known for every k-opt neighborhood with k ≥ 3, so our result for $2$-opt completes the picture for all k-kopt neighborhoods. In (p,q,r)-Maximum Constraint Assignment, each constraint involves at most p variables, each variable occurs in at most q constraints, and each domain has size r. Decreasing any of the parameters of (3,2,2) or (2,3,2) yields a problem in which every sequence of improving flips has polynomial length, so both Maximum Constraint Assignment results are tight. All three results settle long-standing open problems. Our proofs build on a common construction idea, which reveals a close connection between the local-search dynamics of the three problems.
ER  -