Minimum Reload Cost Graph Factors

  • Julien Baste
  • Didem Gözüpek
  • Mordechai ShalomEmail author
  • Dimitrios M. Thilikos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11376)


The concept of Reload cost in a graph refers to the cost that occurs while traversing a vertex via two of its incident edges. This cost is uniquely determined by the colors of the two edges. This concept has various applications in transportation networks, communication networks, and energy distribution networks. Various problems using this model are defined and studied in the literature. The problem of finding a spanning tree whose diameter with respect to the reload costs is the smallest possible, the problems of finding a path, trail or walk with minimum total reload cost between two given vertices, problems about finding a proper edge coloring of a graph such that the total reload cost is minimized, the problem of finding a spanning tree such that the sum of the reload costs of all paths between all pairs of vertices is minimized, and the problem of finding a set of cycles of minimum reload cost, that cover all the vertices of a graph, are examples of such problems. In this work we focus on the last problem. Noting that a cycle cover of a graph is a 2-factor of it, we generalize the problem to that of finding an r-factor of minimum reload cost of an edge colored graph. We prove several NP-hardness results for special cases of the problem. Namely, bounded degree graphs, planar graphs, bounded total cost, and bounded number of distinct costs. For the special case of \(r=2\), our results imply an improved NP-hardness result. On the positive side, we present a polynomial-time solvable special case which provides a tight boundary between the polynomial and hard cases in terms of r and the maximum degree of the graph. We then investigate the parameterized complexity of the problem, prove W[1]-hardness results and present an FPT-algorithm.


Parameterized complexity Graph factors Reload costs 


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Authors and Affiliations

  1. 1.Institut für Optimierung und Operations ResearchUniversität UlmUlmGermany
  2. 2.Department of Computer EngineeringGebze Technical UniversityGebzeTurkey
  3. 3.TelHai CollegeUpper GalileeIsrael
  4. 4.AlGCo project-team, LIRMM, CNRS, Université de MontpellierMontpellierFrance
  5. 5.Department of MathematicsNational and Kapodistrian University of AthensAthensGreece

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