Package: quicopt 0.1.1

Tim Bode

quicopt: Client for the 'Quicopt' Optimization Service

Author an optimization model — including a model under uncertainty, with random variables, expectations, conditional value at risk and chance constraints — in a native R interface, and solve it with the 'Quicopt' service <https://quicopt.com>. Models are encoded to the service's wire format and solved remotely; no solver is installed locally. Random variables carry distributions or empirical scenario columns taken directly from a data frame, so observed history becomes a stochastic program in one call.

Authors:Tim Bode [aut, cre, cph]

quicopt_0.1.1.tar.gz
quicopt_0.1.1.zip(r-4.7-any)quicopt_0.1.1.zip(r-4.6-any)
quicopt_0.1.1.tar.gz(r-4.7-any)quicopt_0.1.1.tar.gz(r-4.6-any)
quicopt_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
quicopt/json (API)

# Install 'quicopt' in R:

install.packages('quicopt', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/quicopt/quicopt-r/issues

Pkgdown/docs site:https://quicopt.github.io

On CRAN:

2.70 score 47 exports 2 dependencies

Last updated from:d65a55457f. Checks:6 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	105
source / vignettes	OK	194
linux-release	OK	119
windows-devel	OK	84
windows-release	OK	67
wasm-release	OK	86

Exports:add add_rand_var add_var as_program bin_var BINARY constraint CONTINUOUS cvar DEFAULT_BASE_URL distribution empirical encode encode_params expectation index_set indicator int_var INTEGER ir_apply ir_const ir_param ir_reduce ir_set_ref ir_source_ref ir_var job_delete job_log job_result job_status maximize minimize model nonneg normal num_var parametric prob program rand_var set_distribution set_empirical set_scenarios solve_model submit var_decl zero

Dependencies:curl jsonlite

Deciding before the data arrives

The newsvendor | Optimizing the tail instead of the average | From observed history | What comes back

Rendered fromstochastic.Rmdusingknitr::rmarkdown

Last update: 2026-10-14
Started: 2026-10-14

Help page	Topics
Add constraints to a model	add
Lower a model to a program	as_program
Constraint sets	consets indicator nonneg zero
A constraint row	constraint
A variable declaration	BINARY CONTINUOUS INTEGER var_decl
The conditional value at risk at level 'alpha'	cvar
The public Quicopt endpoint	DEFAULT_BASE_URL
Distributions for random variables	distribution normal
A random variable given as a fixed scenario column	empirical
Encode a program to the bytes the service reads	encode
Encode parameter tables alone, for rebinding data	encode_params
The expected value over the scenarios	expectation
quicopt expressions — model arithmetic in plain R	expressions
A named index set with concrete elements	index_set
quicopt IR — a model as plain data	ir ir_apply ir_const ir_param ir_reduce ir_set_ref ir_source_ref ir_var
Poll a submitted job	job_delete job_log job_result job_status
State what the model optimizes	maximize minimize
Create an empty optimization model	model
Declare decision variables	add_var bin_var int_var num_var
A random variable drawn from a distribution	parametric
The probability that a comparison holds	prob
A complete optimization model as plain data	program
Declare a random variable	add_rand_var rand_var
Give a random variable its distribution	set_distribution
Turn observed history into a model's uncertainty	set_empirical
Set how many scenarios are drawn, and from which seed	set_scenarios
Solve a model with the Quicopt service	solve.quicopt_model solve_model
Optimization under uncertainty	stochastic
Submit a model for asynchronous solving	submit
quicopt wire — a program's bytes	wire

Package: quicopt 0.1.1

quicopt: Client for the 'Quicopt' Optimization Service

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)