Package index

Authoring a model

model()

Create an empty optimization model

num_var() int_var() bin_var() add_var()

Declare decision variables

minimize() maximize()

State what the model optimizes

add()

Add constraints to a model

expressions

quicopt expressions — model arithmetic in plain R

Uncertainty

stochastic

Optimization under uncertainty

rand_var() add_rand_var()

Declare a random variable

set_distribution()

Give a random variable its distribution

set_scenarios()

Set how many scenarios are drawn, and from which seed

set_empirical()

Turn observed history into a model's uncertainty

distribution() normal()

Distributions for random variables

empirical()

A random variable given as a fixed scenario column

expectation()

The expected value over the scenarios

cvar()

The conditional value at risk at level alpha

prob()

The probability that a comparison holds

Solving

solve_model() solve(<quicopt_model>)

Solve a model with the Quicopt service

submit()

Submit a model for asynchronous solving

job_status() job_result() job_log() job_delete()

Poll a submitted job

DEFAULT_BASE_URL

The public Quicopt endpoint

The program and its bytes

program()

A complete optimization model as plain data

CONTINUOUS INTEGER BINARY var_decl()

A variable declaration

index_set()

A named index set with concrete elements

constraint()

A constraint row

zero() nonneg() indicator()

Constraint sets

parametric()

A random variable drawn from a distribution

ir_const() ir_param() ir_var() ir_apply() ir_reduce() ir_source_ref() ir_set_ref()

quicopt IR — a model as plain data

wire

quicopt wire — a program's bytes

encode()

Encode a program to the bytes the service reads

encode_params()

Encode parameter tables alone, for rebinding data

as_program()

Lower a model to a program