Download e-book for kindle: A Reformulation-Linearization Technique for Solving Discrete by Hanif D. Sherali,W. P. Adams

By Hanif D. Sherali,W. P. Adams

ISBN-10: 1441948082

ISBN-13: 9781441948083

This booklet offers with the idea and purposes of the Reformulation- Linearization/Convexification process (RL T) for fixing nonconvex optimization difficulties. A unified remedy of discrete and non-stop nonconvex programming difficulties is gifted utilizing this technique. In essence, the bridge among those different types of nonconvexities is made through a polynomial illustration of discrete constraints. for instance, the binariness on a 0-1 variable x . could be equivalently J expressed because the polynomial constraint x . (1-x . ) = zero. the inducement for this publication is J J the function of tight linear/convex programming representations or relaxations in fixing such discrete and non-stop nonconvex programming difficulties. The critical thrust is to start with a version that presents an invaluable illustration and constitution, after which to extra develop this illustration via automated reformulation and constraint iteration strategies. As pointed out above, the point of interest of this publication is the improvement and alertness of RL T to be used as an automated reformulation technique, and in addition, to generate robust legitimate inequalities. The RLT operates in levels. within the Reformulation part, specific sorts of extra implied polynomial constraints, that come with the aforementioned constraints on the subject of binary variables, are appended to the matter. The ensuing challenge is as a result linearized, other than that definite convex constraints are often retained in XV specific specific circumstances, within the Linearization/Convexijication section. this can be performed through the definition of appropriate new variables to exchange each one certain variable-product time period. the better dimensional illustration yields a linear (or convex) programming relaxation.

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A Reformulation-Linearization Technique for Solving Discrete and Continuous Nonconvex Problems (Nonconvex Optimization and Its Applications) by Hanif D. Sherali,W. P. Adams


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