Journal of Optimization Theory and Applications

, Volume 178, Issue 2, pp 538–559 | Cite as

An Algorithm for Solving the Shortest Path Improvement Problem on Rooted Trees Under Unit Hamming Distance

  • Binwu Zhang
  • Xiucui GuanEmail author
  • Panos M. Pardalos
  • Chunyuan He


Shortest path problems play important roles in computer science, communication networks, and transportation networks. In a shortest path improvement problem under unit Hamming distance, an edge-weighted graph with a set of source–terminal pairs is given. The objective is to modify the weights of the edges at a minimum cost under unit Hamming distance such that the modified distances of the shortest paths between some given sources and terminals are upper bounded by the given values. As the shortest path improvement problem is NP-hard, it is meaningful to analyze the complexity of the shortest path improvement problem defined on rooted trees with one common source. We first present a preprocessing algorithm to normalize the problem. We then present the proofs of some properties of the optimal solutions to the problem. A dynamic programming algorithm is proposed for the problem, and its time complexity is analyzed. A comparison of the computational experiments of the dynamic programming algorithm and MATLAB functions shows that the algorithm is efficient although its worst-case complexity is exponential time.


Shortest path problem Rooted trees Network improvement problem Hamming distance Dynamic programming 

Mathematics Subject Classification

90C27 90C35 90C39 



This work was supported by the National Natural Science Foundation of China (11471073) and Chinese Universities Scientific Fund (2015B27914). The work of P.M. Pardalos was conducted at the National Research University Higher School of Economics and supported by the RSF Grant 14-41-00039.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Binwu Zhang
    • 1
  • Xiucui Guan
    • 2
    Email author
  • Panos M. Pardalos
    • 3
    • 4
  • Chunyuan He
    • 1
  1. 1.Department of Mathematics and PhysicsHohai UniversityChangzhouChina
  2. 2.School of MathematicsSoutheast UniversityNanjingChina
  3. 3.Department of Industrial and Systems Engineering, Center for Applied OptimizationUniversity of FloridaGainesvilleUSA
  4. 4.LATNAHigher School of EconomicsMoscowRussia

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