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Title: | Parameterized Complexity of the Hiding Leader problem |
Authors: | MAITY, SOUMEN KARRA, MOHAN Dept. of Mathematics 20161105 |
Keywords: | parameterized complexity Kernelization Social Network Analysis Hiding Leader Independent set Fixed-parameter Tractable W-[1]-hard |
Issue Date: | Jan-2023 |
Citation: | 72 |
Abstract: | In this thesis, we study the theory of parametrized complexity and examine parameterized complexity of the Hiding Leader problem. We discuss standard tools and techniques for showing the fixed-parameter tractability of parameterized problems like kernelization and branching. We review fixed-parameter intractability and show, using parameterized reductions and W-hierarchy, that some problems are unlikely to be fixed-parameter tractable. Given a graph G = (V,E), a subset L ⊆ V of leaders, an integer k that denotes the maximum number of edges that we are allowed to add in G, an integer d that denotes the least number of followers in F = V \ L whose final centrality should be at least as high as any leader, the goal is to compute if there exists a subset W ⊆ F × F such that (i) |W| ≤ k, and (ii) there exists a F′ ⊆ F with |F′| ≥ d satisfying c(G′, f) ≥ c(G′, ℓ) for all f ∈ F′ and ℓ ∈ L where G′ = (V,E ∪ W). We study the parameterized complexity of the problem in the setting of degree centrality for a few sets of parameters and shed light on its fixed-parameter intractability using tools discussed apriori. We obtain the following results for the Hiding Leader problem: 1. The Hiding Leader problem is W[1]-hard when parameterized by d + k. Therefore, the problem is W[1]-hard when parameterized by only d or k. 2. The Hiding Leader problem admits a kernel of size (d − 1)(Δ + 1) + 1, where Δ denotes the maximum degree of G. 3. The Hiding Leader problem in the setting of core centrality is W[1]-hard when parameterized by k + d. 4. Finally, we briefly touch upon the problem and some results in the core-centrality setting. xi |
URI: | http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/7553 |
Appears in Collections: | MS THESES |
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20161105_Mohan_Karra_MS_Thesis.pdf | MS Thesis | 708.37 kB | Adobe PDF | View/Open |
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