Mohammad Khairul Hasan

Approximation algorithms for connected facility location problems

Abstract We study Connected Facility Location problems. We are given a connected graph G=(V,E) with nonnegative edge cost ce for each edge e∈E, a set of clients D⊆V such that each client j∈D has positive demand dj and a set of facilities F⊆V each has nonnegative opening cost fi and capacity to serve all client demands. The objective is to open a subset of facilities, say

Improved Primal-Dual Approximation Algorithm for the Connected Facility Location Problem

\hat{F}

Probabilistic cost model for nearest neighbor search in image retrieval

, to assign each client j∈D to exactly one open facility i(j) and to connect all open facilities by a Steiner tree T such that the cost

Improved approximation algorithm for connected facility location problems

\sum_{i\in \hat{F}}f_{i}+\sum_{j\in D}d_{j}c_{i(j)j}+M\sum_{e\in T}c_{e}

Approximation algorithms for the Weighted t-Uniform Sparsest Cut and some other graph partitioning problems

is minimized for a given input parameter M≥1. We propose a LP-rounding based 8.29 approximation algorithm which improves the previous bound 8.55 (Swamy and Kumar in Algorithmica, 40:245–269, 2004). We also consider the problem when opening cost of all facilities are equal. In this case we give a 7.0 approximation algorithm.

Bounds on the Geometric Mean of Arc Lengths for Bounded-Degree Planar Graphs

In the Connected Facility Location(ConFL) problem, we are given a graph G= (V, E) with nonnegative edge cost c e on the edges, a set of facilities

A 6.55 factor primal-dual approximation algorithm for the connected facility location problem

\mathcal{F}\subset V

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, a set of demands, i.e., clients

Improved Approximation Algorithm for Connected Facility Location Problems (Extended Abstract)

\mathcal{D}\subset V