LaGO-a (heuristic) Branch and Cut algorithm for nonconvex MINLPs

作者: Turang Ahadi-Oskui , Stefan Vigerske , Ivo Nowak , Georgios Tsatsaronis

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摘要: The paper examines the applicability of mathematical programming methods to the simultaneous optimization of the structure and the operational parameters of a combined-cycle-based cogeneration plant. Thus, the optimization problem is formulated as a highly non-convex mixed-integer nonlinear problem (MINLP) and solved by the MINLP solver LaGO. The algorithm generates a convex relaxation of the MINLP and applies a Branch and Cut algorithm to the relaxation. Numerical results for different demands for electric power and process steam are discussed and a sensitivity analysis is performed.

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