Final Report-Optimization Under Uncertainty and Nonconvexity: Algorithms and Software

Jeff Linderoth

关键词: ALGORITHMS;    FOCUSING;    OPTIMIZATION;    SYMMETRY;    COMPUTER CODES Numerical Optimization;    Stochastic Programming;    Mixed Integer Linear Programming;    Mixed Integer Nonlinear Programming;   

DOI  :  10.2172/939366
RP-ID  :  DOE/ER/25694-1
PID  :  OSTI ID: 939366
Others  :  TRN: US201010%%420

学科分类：数学（综合）

美国|英语

来源: SciTech Connect

【 摘 要 】

The goal of this research was to develop new algorithmic techniques for solving large-scale numerical optimization problems, focusing on problems classes that have proven to be among the most challenging for practitioners: those involving uncertainty and those involving nonconvexity. This research advanced the state-of-the-art in solving mixed integer linear programs containing symmetry, mixed integer nonlinear programs, and stochastic optimization problems.