We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the… (More)

We present a general approximation technique for a large class of graph problems. Our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph with trees, cycles or… (More)

We present randomized approximation algorithms for the MAX CUT and MAX 2SAT problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a… (More)

Discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling, facility location, and network design; to computer science problems in… (More)

We study optimization problems that may be expressed as “Boolean constraint satisfaction problems.” An instance of a Boolean constraint satisfaction problem is given by m constraints applied to n… (More)

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In this paper, we give a 9.28-approximation algorithm for the minimum latency problem that uses only <i>O</i>(<i>n</i> log <i>n</i>) calls to the prize-collecting Steiner tree (PCST) subroutine of… (More)

MAX SAT (the maximum s~tisfiability problem) is stated as follows: given a set of clauses with weights, find a truth assignment that maximizes the sum of the weights of the satisfied clauses. In this… (More)

We consider a class of network design problems in which one needs to nd a minimum-cost network satisfying certain connectivity requirements. For example, in the sur-vivable network design problem,… (More)