The well-known Max Cut problem asks for the largest bipartite subgraph of a graph G. This problem has been the subject of extensive research, both from the algorithmic perspective in computer science and the extremal perspective in combinatorics. Let n be the number of vertices and e be the number edges of G and let b(G) denote the size of the largest bipartite subgraph of G. The extremal part ...

We analyze the addition of a simple local improvement step to various known ran-domized approximation algorithms. Let ' 0:87856 denote the best approximation ratio currently known for the Max Cut problem on general graphs GW95]. We consider a semideenite relaxation of the Max Cut problem, round it using the random hyperplane rounding technique of ((GW95]), and then add a local improvement step....

This paper studies the existence of eecient (small size) ampliiers for proving explicit inaproximability results for bounded degree and bounded occurrence combinatorial optimization problems, and gives an explicit construction for such ampliiers. We use this construction to improve the currently best known approximation lower bounds for bounded occurrence instances of linear equations mod 2, an...

Metric MAX-CUT is the problem of dividing a set of points in metric space into two parts so as to maximize the sum of the distances between points belonging to distinct parts. We show that metric MAX-CUT has a polynomial time randomized approximation scheme.

a new parametric model was developed for predicting cut point of hydraulic classifiers. the model directly uses operating parameters including pulp flowrate, feed particle size characteristics, pulp solids content, solid density and particles retention time in the classification chamber and also covers uncontrollable errors using calibration constants. the model applicability was first verified...