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Page 2 Lecture Notes in Computer Science 2865 Edited by G. Goos ...

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190 S.O. Krumke et al.2.2 Bicriteria ApproximationOur results for the diameter problem use the bicriteria approximation frameworkdeveloped <strong>in</strong> [11] for deal<strong>in</strong>g with computationally <strong>in</strong>tractable optimizationproblems <strong>in</strong>volv<strong>in</strong>g two objectives. We recall the relevant def<strong>in</strong>itions and notation.Def<strong>in</strong>ition 2. Suppose a problem Π with two m<strong>in</strong>imization objectives A and Bis posed <strong>in</strong> the follow<strong>in</strong>g manner: Given a budget constra<strong>in</strong>t on objective A, f<strong>in</strong>d asolution which m<strong>in</strong>imizes the value of objective B among all solutions satisfy<strong>in</strong>gthe budget constra<strong>in</strong>t. An (α, β)-approximation algorithm for problem Π isa polynomial time algorithm that provides for every <strong>in</strong>stance of Π a solutionsatisfy<strong>in</strong>g the follow<strong>in</strong>g two conditions.1. The solution violates the budget constra<strong>in</strong>t on objective A <strong>by</strong> a factor of atmost α.2. The value of objective B <strong>in</strong> the solution is with<strong>in</strong> a factor of at most β ofthe m<strong>in</strong>imum possible value satisfy<strong>in</strong>g the budget constra<strong>in</strong>t.We note that 〈Undir, Diameter, TotalP〉 is an example of an optimizationproblem with two objectives. In this problem, diameter of the <strong>in</strong>duced graphand total power serve as the budgeted objective (with budget D) and the m<strong>in</strong>imizationobjective respectively. Thus, an (α, β)-approximation algorithm for theproblem provides a solution where the <strong>in</strong>duced graph has diameter at most αD,and the total power assigned is with<strong>in</strong> a factor β of the m<strong>in</strong>imum total powerneeded to <strong>in</strong>duce a graph with diameter at most D.To obta<strong>in</strong> bicriteria approximation algorithms for the 〈Undir, Diameter,TotalP〉 problem, we rely on known approximation results for anotherproblem, called M<strong>in</strong>imum Cost Tree with a Diameter Constra<strong>in</strong>t(Mctdc), also <strong>in</strong>volv<strong>in</strong>g two m<strong>in</strong>imization objectives. A formal def<strong>in</strong>ition of thisproblem is as follows.M<strong>in</strong>imum Cost Tree with a Diameter Constra<strong>in</strong>t (Mctdc)Instance: A connected undirected graph G(V,E), a nonnegative weight w(e) foreach edge e ∈ E, an <strong>in</strong>teger δ ≤ n − 1.Requirement: F<strong>in</strong>d an edge subgraph T (V,E T )ofG such that T (V,E T ) is a tree,Dia(T ) ≤ δ and the total weight of the edges <strong>in</strong> E T is the smallest among allthe trees satisfy<strong>in</strong>g the diameter constra<strong>in</strong>t.Mctdc is known to be NP-hard [11]. Bicriteria approximations for this problemhave been presented <strong>in</strong> [2,9,11]. These results are used <strong>in</strong> Section 4.3 Summary of Results and Related Work3.1 Summary of ResultsThe follow<strong>in</strong>g are the ma<strong>in</strong> results presented <strong>in</strong> this paper. For all the problems,n denotes the number of transceivers <strong>in</strong> the problem <strong>in</strong>stance.

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