Title | Generalized branch-and-cut framework for mixed-integer nonlinear optimization problems |
Publication Type | Journal Article |
Year of Publication | 2000 |
Authors | Kesavan P, Barton PI |
Journal | Computers & Chemical Engineering |
Volume | 24 |
Pagination | 1361 - 1366 |
ISSN | 0098-1354 |
Keywords | Decomposition heuristics |
Abstract | Branch and bound ({BB}) is the primary deterministic approach that has been applied successfully to solve mixed-integer nonlinear programming ({MINLPs}) problems in which the participating functions are nonconvex. Recently, a decomposition algorithm was proposed to solve nonconvex MINLPs. In this work, a generalized branch and cut ({GBC}) algorithm is proposed and it is shown that both decomposition and BB algorithms are specific instances of the {GBC} algorithm with a certain set of heuristics. This provides a unified framework for comparing {BB} and decomposition algorithms. Finally, a set of heuristics which may be potentially more efficient computationally compared to all currently available deterministic algorithms is presented. |
URL | http://www.sciencedirect.com/science/article/B6TFT-448HNR0-67/2/40524d47f38c8f220350b3d6fb1f6012 |
DOI | 10.1016/S0098-1354(00)00421-X |
Generalized branch-and-cut framework for mixed-integer nonlinear optimization problems
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