1990
DOI: 10.1002/net.3230200305
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Fair dissections of spiders, worms, and caterpillars

Abstract: In the present paper we deal with equipartition problems for special classes of trees, i.e., spiders, stars, worms, and caterpillars. We prove that the equipartition problem is NP-complete for spiders (and, hence, for general trees); on the other hand, we give efficient polynomial-time algorithms for stars, worms, and caterpillars.

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Cited by 26 publications
(14 citation statements)
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“…In particular, we observe that optimization problem (11) can be formulated as a graph partitioning (GP) problem. We also observe that because of the special topology of the problem at hand, this problem is polynomially solvable [19], [20]. We will first discuss how the physical wireless system entities can be represented in a graph setting.…”
Section: (9)mentioning
confidence: 99%
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“…In particular, we observe that optimization problem (11) can be formulated as a graph partitioning (GP) problem. We also observe that because of the special topology of the problem at hand, this problem is polynomially solvable [19], [20]. We will first discuss how the physical wireless system entities can be represented in a graph setting.…”
Section: (9)mentioning
confidence: 99%
“…Although the problem of optimally partitioning an arbitrary graph with an arbitrary cost function is an NP-hard optimization problem, partitioning a string optimally with a separable cost function can be solved in polynomial time. We use the following optimal graph partitioning result presented in [20].…”
Section: Optimal Partitioning and Shortest Path Algorithmsmentioning
confidence: 99%
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“…Specifically, the optimization problem in (4) can be transformed into a graph partitioning problem following the approach in reference [11] , as described next.…”
Section: ⅲ Optimum Schedulingmentioning
confidence: 99%
“…In this case, the problem of graph partitioning of a string can be reduced to a shortest path problem with complexity O(LT 2 ) [13]. In the following, the solution by a shortest path algorithm is described.…”
Section: Optimum Schedulementioning
confidence: 99%