Index

A | B | C | D | E | F | G | H | I | J | L | M | N | O | P | Q | R | S | T | U | V

A

attaching
streams

B

basic
solution
basis identification, [1]
basis type
sensitivity analysis
BLAS
bound
constraint, [1], [2]
linear optimization
variable, [1], [2]

C

callback
CBF format
certificate
dual, [1], [2], [3]
primal, [1], [2]
Cholesky factorization
column ordered
matrix format
complementarity
cone
dual
quadratic, [1]
rotated quadratic, [1]
semidefinite, [1]
conic optimization, [1]
infeasibility
interior-point
termination criteria
conic problem
example
conic quadratic optimization
Conic quadratic reformulation
constraint
bound, [1], [2]
linear optimization
matrix, [1], [2]
quadratic
constraints
lower limit
upper limit
convex interior-point
optimizers
cqo1
example
cut

D

decision
variables
defining
objective
determinism, [1]
dual
certificate, [1], [2], [3]
cone
feasible
infeasible, [1], [2], [3], [4]
problem, [1], [2]
solution
variable, [1]
duality
conic
gap
linear
semidefinite
dualizer

E

eliminator
error
optimization
errors
example
conic problem
cqo1
lo1
qo1
quadratic objective, [1]
exceptions

F

factor model
feasible
dual
primal, [1], [2]
problem
format
CBF
LP
MPS
OPF
OSiL
json
sol
task
full
vector format

G

gap
duality

H

hot-start

I

I/O
infeasibility, [1], [2], [3]
conic optimization
linear optimization
semidefinite
infeasible
dual, [1], [2], [3], [4]
primal, [1], [2], [3], [4], [5]
problem, [1], [2], [3]
infeasible problems
information item, [1]
installation
IronPython
Mono
Visual Studio
nmake (command)
requirements
troubleshooting
integer
optimizer
solution
variable
integer feasible
solution
integer optimization, [1]
cut
delayed termination criteria
initial solution
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]
interior-point optimizer
IronPython
installation

J

json format

L

LAPACK
license
linear
objective
linear constraint matrix
linear dependency
linear optimization, [1]
bound
constraint
infeasibility
interior-point
objective
simplex
termination criteria, [1]
variable
linearity interval
lo1
example
logging
integer optimizer
interior-point, [1]
optimizer, [1], [2]
simplex
lower limit
constraints
variables
LP format

M

Markowitz
model
Markowitz model
portfolio optimization
matrix
constraint, [1], [2]
semidefinite
symmetric
matrix format
column ordered
row ordered
triplets
memory management
MIP
see integer optimization
mixed-integer
see integer
mixed-integer optimization
see integer optimization
model
Markowitz
portfolio optimization
modelling
design
Mono
installation
MPS format
free

N

near-optimal
solution, [1], [2], [3]
nmake (command)
installation
numerical issues
presolve
scaling
simplex

O

objective
defining
linear
linear optimization
objective bound
objective vector
OPF format
optimal
solution, [1]
optimality gap
optimization
conic quadratic
error
linear, [1]
semidefinite
optimizer
determinism, [1]
integer
interior-point, [1]
interrupt
logging, [1], [2]
parallelization
selection, [1]
simplex
optimizers
convex interior-point
OSiL format

P

pair sensitivity analysis
optimal partition type
parallelization, [1]
parameter
integer optimization
simplex
portfolio optimization
model
positive semidefinite
presolve
eliminator
linear dependency check
numerical issues
primal
certificate, [1], [2]
feasible, [1], [2]
infeasible, [1], [2], [3], [4], [5]
problem, [1], [2]
solution, [1]
primal-dual
problem, [1]
solution
problem
dual, [1], [2]
feasible
infeasible, [1], [2], [3]
load
primal, [1], [2]
primal-dual, [1]
save
status
unbounded

Q

qo1
example
quadratic
constraint
quadratic cone, [1]
quadratic objective
example, [1]
quadratic optimization
quality
solution

R

relaxation
response code
rotated quadratic cone, [1]
row ordered
matrix format

S

scaling
scopt
semidefinite
cone, [1]
infeasibility
matrix
variable, [1]
semidefinite optimization, [1]
sensitivity analysis
basis type
separable convex optimization
shadow price
simplex
linear optimization
logging
numerical issues
optimizer
parameter
termination criteria
sol format
solution
basic
dual
file format
integer
integer feasible
interior-point
near-optimal, [1], [2], [3]
optimal, [1]
primal, [1]
primal-dual
quality
retrieve
status, [1]
solving linear system
sparse
vector format
sparse vector
status
problem
solution, [1]
streams
attaching
symmetric
matrix

T

task format
termination
termination criteria
conic optimization
delayed
integer optimization
interior-point, [1]
linear optimization, [1]
simplex
tolerance, [1], [2]
thread, [1]
time limit
tolerance
integer optimization
termination criteria, [1], [2]
triplets
matrix format
troubleshooting
installation

U

unbounded
problem
upper limit
constraints
variables
user callback
see callback

V

variable
bound, [1], [2]
dual, [1]
integer
linear optimization
semidefinite, [1]
variables
decision
lower limit
upper limit
vector format
full
sparse
Visual Studio
installation