Navigation
index
symbols
|
Fusion API for Python 9.3.20
»
Index
Index
A
|
B
|
C
|
D
|
E
|
F
|
G
|
H
|
I
|
J
|
L
|
M
|
N
|
O
|
P
|
Q
|
R
|
S
|
T
|
U
|
V
A
algorithm
approximation
,
[1]
approximation
algorithm
,
[1]
correlation matrix
asset
see portfolio optimization
assignment problem
B
basic
solution
basis identification
bound
constraint
,
[1]
,
[2]
,
[3]
,
[4]
linear optimization
variable
,
[1]
,
[2]
,
[3]
,
[4]
C
callback
cardinality constraints
,
[1]
CBF format
certificate
dual
,
[1]
primal
,
[1]
Cholesky factorization
complementarity
,
[1]
cone
dual
dual exponential
exponential
power
,
[1]
quadratic
rotated quadratic
semidefinite
conic exponential optimization
conic optimization
,
[1]
,
[2]
,
[3]
interior-point
modeling
termination criteria
conic quadratic optimization
constraint
bound
,
[1]
,
[2]
,
[3]
,
[4]
linear optimization
matrix
,
[1]
,
[2]
modeling
correlation matrix
,
[1]
approximation
covariance matrix
see correlation matrix
cut
D
denoising
dense
matrix
determinant
determinism
dual
certificate
,
[1]
cone
feasible
infeasible
,
[1]
,
[2]
problem
,
[1]
,
[2]
solution
,
[1]
,
[2]
,
[3]
variable
,
[1]
duality
conic
linear
semidefinite
dualizer
E
efficient frontier
elastic net
eliminator
ellipsoid
entropy
relative
error
optimization
errors
exceptions
exponential
exponential cone
expression
modeling
F
factor model
,
[1]
feasibility problem
feasible
dual
primal
,
[1]
,
[2]
problem
format
CBF
json
LP
MPS
OPF
PTF
sol
task
Frobenius norm
Fusion
reformulation
G
geometric mean
,
[1]
geometric programming
GP
H
hot-start
I
I/O
infeasibility
,
[1]
,
[2]
linear optimization
semidefinite
infeasible
dual
,
[1]
,
[2]
primal
,
[1]
,
[2]
,
[3]
,
[4]
problem
,
[1]
,
[2]
information item
,
[1]
installation
Conda
PIP
requirements
setup script
troubleshooting
integer
optimizer
solution
variable
integer feasible
solution
integer optimization
,
[1]
cut
initial solution
,
[1]
objective bound
optimality gap
parameter
relaxation
termination criteria
tolerance
integer optimizer
logging
interior-point
conic optimization
linear optimization
logging
,
[1]
optimizer
,
[1]
solution
termination criteria
,
[1]
J
json format
L
lasso
least squares
integer
license
checkout
parameter
path
limitations
linear constraint matrix
linear dependency
linear optimization
,
[1]
bound
constraint
infeasibility
interior-point
objective
simplex
termination criteria
,
[1]
variable
log-sum-exp
,
[1]
logarithm
logging
integer optimizer
interior-point
,
[1]
optimizer
,
[1]
,
[2]
simplex
logistic regression
Löwner-John ellipsoid
LP format
M
machine learning
large margin classification
logistic regression
separating hyperplane
Support-Vector Machine
makespan
market impact cost
Markowitz model
matrix
constraint
,
[1]
,
[2]
dense
low rank
modeling
semidefinite
sparse
symmetric
memory management
MIP
see integer optimization
mixed-integer
see integer
mixed-integer optimization
see integer optimization
modeling
conic optimization
constraint
design
expression
matrix
objective
variable
monomial
MPS format
free
N
near-optimal
solution
norm
1-norm
2-norm
Frobenius
nuclear
p-norm
nuclear norm
numerical issues
presolve
scaling
simplex
numpy
O
objective
,
[1]
linear optimization
modeling
objective bound
OPF format
optimal
solution
optimality gap
optimization
conic
conic quadratic
error
linear
,
[1]
semidefinite
optimizer
determinism
integer
interior-point
,
[1]
interrupt
,
[1]
logging
,
[1]
,
[2]
selection
,
[1]
simplex
time limit
Optimizer API
reformulation
P
parallelization
parameter
integer optimization
license
simplex
parameters
parametrization
Pareto optimality
path
license
penalty
portfolio optimization
cardinality constraints
,
[1]
correlation matrix
efficient frontier
factor model
,
[1]
market impact cost
Markowitz model
Pareto optimality
slippage cost
transaction cost
power
power cone
,
[1]
power cone optimization
presolve
eliminator
linear dependency check
numerical issues
primal
certificate
,
[1]
feasible
,
[1]
,
[2]
infeasible
,
[1]
,
[2]
,
[3]
,
[4]
problem
,
[1]
,
[2]
solution
,
[1]
,
[2]
,
[3]
,
[4]
primal-dual
problem
,
[1]
solution
problem
dual
,
[1]
,
[2]
feasible
infeasible
,
[1]
,
[2]
load
primal
,
[1]
,
[2]
primal-dual
,
[1]
save
status
unbounded
,
[1]
PTF format
Q
quadratic cone
quality
solution
R
regression
logistic
regularization
relaxation
,
[1]
reoptimization
,
[1]
,
[2]
response code
ridge
rotated quadratic cone
S
scaling
scheduling
Schur complement
semicontinuous variable
semidefinite
cone
infeasibility
matrix
variable
semidefinite optimization
,
[1]
separating hyperplane
setup script
simplex
linear optimization
logging
numerical issues
optimizer
parameter
termination criteria
slice
variable
,
[1]
,
[2]
slippage cost
softplus
sol format
solution
basic
dual
,
[1]
,
[2]
,
[3]
file format
integer
integer feasible
interior-point
near-optimal
optimal
primal
,
[1]
,
[2]
,
[3]
,
[4]
primal-dual
quality
retrieve
status
sparse
matrix
stacking
status
problem
solution
symmetric
matrix
T
task format
termination
termination criteria
conic optimization
integer optimization
interior-point
,
[1]
linear optimization
,
[1]
simplex
tolerance
,
[1]
,
[2]
thread
,
[1]
time limit
,
[1]
tolerance
integer optimization
termination criteria
,
[1]
,
[2]
transaction cost
travelling salesman problem
troubleshooting
installation
U
unbounded
problem
,
[1]
user callback
see callback
V
variable
,
[1]
bound
,
[1]
,
[2]
,
[3]
,
[4]
dual
,
[1]
integer
limitations
linear optimization
modeling
semicontinuous
semidefinite
slice
,
[1]
,
[2]
vectorization
,
[1]
Table of Contents
1 Introduction
2 Contact Information
3 License Agreement
4 Installation
5 Design Overview
6 Conic Modeling
7 Optimization Tutorials
8 Solver Interaction Tutorials
9 Debugging Tutorials
10 Technical guidelines
11 Case Studies
12 Problem Formulation and Solutions
13 Optimizers
14
Fusion
API Reference
15 Supported File Formats
16 List of examples
17 Interface changes
18 Bibliography
Quick search
Download PDF
Modeling Cookbook
Cheatsheet
Navigation
index
symbols
|
Fusion API for Python 9.3.20
»
Index