Solving Pseudo-Convex Mixed Integer Optimization Problems by Cutting Plane Techniques

By T. Westerlund, Ray Pörn. 2002

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Mixed-integer nonlinear optimization*† (2013, methodology): “It also implements methods for MINLPs with pseudoconvex functions (Westerlund and Pörn, 2002).”
MINLP Solver Software (2011, methodology): “In this category we have alphaBB, AlphaECP, AOA, BARON, DICOPT, LaGO, and LindoGlobal.”
Introduction to Global Optimization (2006, unknown): “For example, d.c. optimization and the Extended Cutting Planes (ECP) method [WSHP98, WP02] are structurally diﬀerent from Branch-and-Select approaches; however, both make use of a problem which is already in a special form.”
A review and comparison of solvers for convex MINLP (2018, methodology): “used for terminating the MILP subsolver prematurely presented by [125], usually resulting in only a small portion of the MILP subproblems to be solved to optimality and a significant reduction in the total solution time.”
On the Computational Studies of Deterministic Global Optimization of Head Dependent Short-Term Hydro Scheduling (2013, methodology): “However, several algorithms are available [22]–[24], and implemented into commercial or open MINLP solvers such as DICOPT [25], -ECP and SBB in GAMS, AAOA in AIMMS, MINOPT [26], and BONMIN [27].”