CMU 10-725: Convex Optimization USTC: 最优化原理 Boyd, Vandenberghe, Convex Optimization K. Clarkson (2010), Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm J. Giesen, M. Jaggi and S. Laue, S. (2012), Approximating parametrized convex optimization problems M. Jaggi (2011...
convex equivalence relation 凸等价关系convex function 凸函数convex hull 凸包convex neighborhood 凸邻域convex optimization 凸规划convex polygon 凸多边形convex polyhedron 凸多面体convex programming 凸规划convex sequence 凸序列convex set 凸集convex sublattice 凸子格convex subset 凸子集convex surface 凸面convex ...
CMU 10-725: Convex Optimization USTC: 最优化原理 Boyd, Vandenberghe, Convex Optimization K. Clarkson (2010), Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm J. Giesen, M. Jaggi and S. Laue, S. (2012), Approximating parametrized convex optimization problems M. Jaggi (2011...
一部分 Convex optimization problem 是 tractable 的。 Combinatorial optimization 整数规划很难,整数与连续变量混合的问题(mixed integer programs )很难。 Non-convex optimization 由于可能存在局部最优点等问题,较难解决。但对于一些特定问题,例如 Low-rank approximations and maximum variance,已有可靠的来自于线性代数...
∙GloptiPoly3, by D. Henrion, J.-B. Lasserre and J. Loefberg;a Matlab/SeDuMi add-on for LMI-relaxations of minimization problems over multivariable polynomial functions subject to polynomial or integer constraints. ∙LMITOOL-2.0 of the Optimization and Control Group at ENSTA. ∙...
We study convex optimization problems with side constraints in a multi-class M/G/1 queue with controllable service rates. In the simplest problem of optimizing linear costs with fixed service rate, the cμ rule is known to be optimal. A natural question to ask is whether such simple policies...
We study a class of vector optimization problems with a C-convex objective function under linear constraints. We extend the proximal point algorithm used in scalar optimization to vector optimization. We analyze both the global and local convergence results for the new algorithm. We then apply the...
In recent years, research is very active in nonconvex optimization. There are two principal reasons for this: The first is the importance of its applications to concrete problems in practice. The second is a natural way of leaving the convex optimization (which is sufficiently studied and can ...
两阶段鲁棒优化问题,是多阶段鲁棒优化的一个特例(multi-stage robust optimization)。在两阶段鲁棒优化问题中,一般包含两个不同层级的决策变量,又称为第一阶段的决策(first-stage decision)和第二阶段的决策(second-stage decision)。 战略层决策和战术层决策; 战术层决策和操作层决策; ... 一个典型例子,就是选址...
To solve the JERO models with exponential cones, we develop a second-order conic approximation that limits errors beyond an operating range; with this approach, we can use state-of-the-art second-order conic programming solvers to solve...