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Multi-level Mixed-Integer Optimization

, 2022
This book provides the fundamental underlying mathematical theory, numerical algorithms and effi cient computational tools for the solution of multi-level mixedinteger optimization problems. It can enable a vast array of decision makers and engineers (e.g.
Styliani Avraamidou, E. Pistikopoulos
semanticscholar   +2 more sources

Granularity in Nonlinear Mixed-Integer Optimization

Journal of Optimization Theory and Applications, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
C. Neumann   +2 more
semanticscholar   +4 more sources

Convex mixed-integer optimization with Frank–Wolfe methods

Mathematical Programming Computation, 2022
Mixed-integer nonlinear optimization encompasses a broad class of problems that present both theoretical and computational challenges. We propose a new type of method to solve these problems based on a branch-and-bound algorithm with convex node ...
Deborah Hendrych   +3 more
semanticscholar   +1 more source

A Two-Timescale Duplex Neurodynamic Approach to Mixed-Integer Optimization

IEEE Transactions on Neural Networks and Learning Systems, 2020
This article presents a two-timescale duplex neurodynamic approach to mixed-integer optimization, based on a biconvex optimization problem reformulation with additional bilinear equality or inequality constraints.
Hangjun Che, Jun Wang
semanticscholar   +1 more source

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