Sartaj K. Sahni, Teofilo F. Gonzalez
Abstract
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For P-complete problems such as traveling salesperson, cycle covers, 0-1 integer programming, multicommodity network flows, quadratic assignment, etc., it is shown that the approximation problem is also P-complete. In contrast with these results, a linear time approximation algorithm for the clustering problem is presented.
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For P-complete problems such as traveling salesperson, cycle covers, 0-1 integer programming, multicommodity network flows, quadratic assignment, etc., it is shown that the approximation problem is also P-complete. In contrast with these results, a linear time approximation algorithm for the clustering problem is presented.
Key concepts: Approximation algorithm, Integer programming, Mathematics, Quadratic equation, Mathematical optimization, Contrast (vision), Integer (computer science), Multi-commodity flow problem