sometimesstudy's Stars
198808xc/Pangu-Weather
An official implementation of Pangu-Weather
altmany/export_fig
A MATLAB toolbox for exporting publication quality figures
sauxpa/ito_diffusions
Library for stochastic process simulation
Grid2op/grid2op
Grid2Op a testbed platform to model sequential decision making in power systems.
meteoinfo/MeteoInfo
MeteoInfo: GIS, scientific computation and visualization environment.
oceanmodeling/adcircpy
Python library for managing input and output files for the ADCIRC model
Gurobi/gurobi-logtools
Extract and visualize information from Gurobi log files
ShusenTang/Dive-into-DL-PyTorch
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
WenYuZhi/LagrangianRelaxationQIP
Lagrangian Relaxation approach solve QIP
pengxiang-liu/benders-decomposition-in-power-system
Application of Benders decomposition in power systems
MuiseDestiny/zotero-style
Ethereal Style for Zotero
hassanmortagy/Electrical-Flows-over-Spanning-Trees
The network reconfiguration problem seeks to find a rooted tree T such that the energy of the (unique) feasible electrical flow over T is minimized. The tree requirement on the support of the flow is motivated by operational constraints in electricity distribution networks. The bulk of existing results on convex optimization over vertices of polytopes and on the structure of electrical flows do not easily give guarantees for this problem, while many heuristic methods have been developed in the power systems community as early as 1989. Our main contribution is to give the first provable approximation guarantees for the network reconfiguration problem. To obtain the result for general graphs, we propose a new method for (approximate) spectral graph sparsification, which may be of independent interest. Using insights from our theoretical results, we propose a general heuristic for the network reconfiguration problem that is orders of magnitude faster than existing methods in the literature, while obtaining comparable performance.
arvinxx/gurobi-official-examples
【中译版】Gurobi 官方教程
Gurobi/modeling-examples
Gurobi modeling examples
wurmen/Gurobi-Python
Learning how to use gurobi with python (in chinese)
Ang-Xuan/CCG-and-Benders-Case-for-Two-stage-Robust-Optimization
复现经典论文《Solving two-stage robust optimization problems using a column-and-constraint generation method》算例
ankurzing/bleaq2
Bilevel Optimization Algorithm
a280558071/CCG-Algorithm-for-TwoStageRobustOptimization
Column and Constraints Generation Algorithm to solve Two-Stage Robust Optimization problems
NREL/virtual-battery-aggregator
benchopt/benchmark_bilevel
Benchmark for bi-level optimization solvers
wanqiuchansheng/sddpy
Python for Stochastic Dual Dynamic Programming Algorithm
XiongPengNUS/rsome
Robust Stochastic Optimization Made Easy
Operations-Research-Science/Ebook-An_introduction_to_robust_optimization
natetsang/optimizing-power-dispatch
This project utilizes convex optimization for optimal dispatch of power systems using convex DistFlow equations and cvxpy.
rwl/PYPOWER
Port of MATPOWER to Python
018/zotdraw
zotero插件,结合excalidraw。无限画布,无限空间。
018/zotcard
ZotCard is a plug-in for Zotero, which is a card note-taking enhancement tool. It provides card templates (such as concept card, character card, golden sentence card, etc., by default, you can customize other card templates), so you can write cards quickly. In addition, it helps you sort cards and standardize card formats.
windingwind/zotero-better-notes
Everything about note management. All in Zotero.
l0o0/jasminum
A Zotero add-on to retrive CNKI meta data. 一个简单的Zotero 插件,用于识别中文元数据
ahmedfgad/GeneticAlgorithmPython
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).