Skip to search form
Skip to main content
Skip to account menu
Semantic Scholar
Semantic Scholar's Logo
Search 225,541,951 papers from all fields of science
Search
Sign In
Create Free Account
Big M method
In operations research, the Big M method is a method of solving linear programming problems using the simplex algorithm. The Big M method extends the…
Expand
Wikipedia
(opens in a new tab)
Create Alert
Alert
Related topics
Related topics
6 relations
Karush–Kuhn–Tucker conditions
Linear programming
List of numerical analysis topics
Operations research
Expand
Broader (1)
Linear algebra
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Constraint Generation for Two-Stage Robust Network Flow Problem To appear in INFORMS Journal on Optimization
D. Simchi-Levi
2018
Corpus ID: 53382833
In this paper, we propose new constraint generation algorithms for solving the two-stage robust minimum cost flow problem, a…
Expand
2017
2017
0 Electric Vehicle Optimized Charge and Drive Management
Korosh Vatanparvar
,
M. A. Faruque
2017
Corpus ID: 38370642
Electric Vehicles (EV) have been considered as a solution to the environmental issues caused by transportation such as air…
Expand
2016
2016
A day-ahead generation scheduling with energy storage considering cycling ramp costs
W. Tan
,
M. Abdullah
,
M. Shaaban
IEEE International Conference on Power and Energy
2016
Corpus ID: 38181064
Variability and uncertainty associated with the growth of variable renewable generation, particularly wind power, introduce…
Expand
2016
2016
Cache-Partitioned Preemption Threshold Scheduling
Z. Gu
,
Chao Wang
,
Haibo Zeng
ACM Transactions on Embedded Computing Systems
2016
Corpus ID: 12227762
For preemptive scheduling with shared cache, different tasks may cause interference in the shared cache, leading to Cache-Related…
Expand
2015
2015
Hybrid stochastic/deterministic unit commitment with wind power generation
W. Tan
,
M. Shaaban
IEEE Eindhoven PowerTech
2015
Corpus ID: 34284269
This paper presents a hybrid stochastic and deterministic unit commitment (SDUC) algorithm which takes into account the…
Expand
2009
2009
MIXED-INTEGER SUPPORT VECTOR MACHINE
Wei Guan
,
Alexander Gray
,
Sven Leyffer
2009
Corpus ID: 14279530
In this paper, we propose a formulation of a feature selecting support vector machine based on the L0-norm regularization. We…
Expand
2008
2008
The Evaluation of Parameter M in the Big M Method of Linear Programming
Yan Yun-sheng
2008
Corpus ID: 124266536
In the simplex method of linear programming,there is a big M method(the penalty factor method) for finding an initial feasible…
Expand
2004
2004
SAT-Based Branch & Bound and Optimal Control of Hybrid Dynamical Systems
A. Bemporad
,
N. Giorgetti
Integration of AI and OR Techniques in Constraint…
2004
Corpus ID: 23125892
A classical hybrid MIP-CSP approach for solving problems having a logical part and a mixed integer programming part is presented…
Expand
2004
2004
An Analysis of the Consistency of Big M Method and Two-Phase Method
Wang Ji-qiang
2004
Corpus ID: 123932892
The consistency of the Big M Method and Two-Phase Method in idea, auxiliary linear programming problem, initial feasible basis…
Expand
2003
2003
An efficient simplex type algorithm for sparse and dense linear programs
K. Paparrizos
,
N. Samaras
,
G. Stephanides
European Journal of Operational Research
2003
Corpus ID: 1709671
By clicking accept or continuing to use the site, you agree to the terms outlined in our
Privacy Policy
(opens in a new tab)
,
Terms of Service
(opens in a new tab)
, and
Dataset License
(opens in a new tab)
ACCEPT & CONTINUE