Package: quicopt 0.7.0

Tim Bode

quicopt: Client for the 'Quicopt' Optimization Service

Write an optimization model in R and solve it with the 'Quicopt' service <https://quicopt.com>: state the decisions, the objective and the constraints, and the service finds the best decision. The model is sent to the service, so no solver needs to be installed. Uncertain data, such as demand or prices, is described by probability distributions or taken from the rows of a data frame, and the model can then minimize an expected cost, guard against bad outcomes, or require a condition to hold with a given probability. Decisions that are an ordering or an assignment, such as a delivery route, can be stated directly.

Authors:Tim Bode [aut, cre, cph]

quicopt_0.7.0.tar.gz
quicopt_0.7.0.zip(r-4.7-any)quicopt_0.7.0.zip(r-4.6-any)quicopt_0.7.0.zip(r-4.5-any)
quicopt_0.7.0.tgz(r-4.6-any)quicopt_0.7.0.tgz(r-4.5-any)
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quicopt_0.7.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
quicopt/json (API)

# Install 'quicopt' in R:
install.packages('quicopt', repos = c('https://quicopt.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:

Conda:

5.00 score 1 stars 92 downloads 82 exports 2 dependencies

Last updated from:1c12e66dcc. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK111
source / vignettesOK184
linux-releaseOK114
macos-releaseOK120
macos-oldrelOK89
windows-develOK66
windows-releaseOK75
windows-oldrelOK88
wasm-releaseOK96

Exports:activeaddadd_part_varadd_perm_varadd_rand_varadd_varas_programbernoullibin_varBINARYblockconstraintCONTINUOUScvarDEFAULT_BASE_URLdistributionempiricalencodeencode_paramsevaluateexpectationexponentialholdsindex_setindicatorint_varINTEGERir_applyir_constir_paramir_reduceir_set_refir_source_refir_struct_refir_table_refir_varis_randomitem_atjob_deletejob_logjob_resultjob_statuslookup_tablemaxmaximizeminminimizemodelnonnegnormalnum_varparametricpart_ofpart_varpartition_declperm_varpermutation_declprecedeprobprodprogramrand_varresamplescenario_maxscenario_minscenario_quantileSEMICONTINUOUSSEMIINTEGERset_distributionset_empiricalset_scenariosset_startsize_ofslot_ofsolve_modelstd_devsubmitsumuniformvar_declvariancezero

Dependencies:curljsonlite

Get started
A first model | Whole numbers | Many decisions at once | Reading the answer | What you can write in an expression | Where the solving happens | Writing a model as a pipe | Where to go next
Rendered fromquicopt.Rmdusingknitr::rmarkdown

Last update: 2026-10-15
Started: 2026-10-05

Deciding before the data arrives
How much to stock | Random variables and scenarios | Planning for the average day | Meeting demand on 90% of days | Checking the answer on new scenarios | A safety margin | Several uncertain quantities | Planning for bad days | Putting a price on an event | Uncertainty from data | Other distributions | Solving again from an earlier answer | Summaries at a glance
Rendered fromstochastic.Rmdusingknitr::rmarkdown

Last update: 2026-10-14
Started: 2026-09-01

Deliveries, fees and teams
A delivery of nothing, or of 10 to 25 units | Warehouses that supply several customers | Splitting into teams | More about these
Rendered fromdeliveries.Rmdusingknitr::rmarkdown

Last update: 2026-10-14
Started: 2026-10-13

Orderings and assignments
A delivery route | Items and slots | The length of the route | Reading the answer | Uncertain travel times | An office plan | A lookup on its own | More about permutations
Rendered frompermutations.Rmdusingknitr::rmarkdown

Last update: 2026-10-14
Started: 2026-10-05

Readme and manuals

Help Manual

Help pageTopics
Whether a variable is in useactive
Add constraints to a modeladd
Convert a model to a programas_program
Group the variables of a subproblemblock
Constraint sets, for building a program by handconsets indicator nonneg zero
A constraint, for building a program by handconstraint
A decision variable, for building a program by handBINARY CONTINUOUS INTEGER SEMICONTINUOUS SEMIINTEGER var_decl
The average over the worst scenarioscvar
The address of the public Quicopt serviceDEFAULT_BASE_URL
Distributions for random variablesbernoulli distribution exponential normal uniform
A random variable given by a sampleempirical
Encode a model as the bytes the service readsencode
Encode parameter tables on their ownencode_params
Compute a quantity at a given solutionevaluate
The average over the scenariosexpectation
Expressions: arithmetic on variablesexpressions
A comparison as a 0/1 expressionholds
An index set, for building a program by handindex_set
Expression nodes, for building a program by handir ir_apply ir_const ir_param ir_reduce ir_set_ref ir_source_ref ir_struct_ref ir_table_ref ir_var
Does an expression vary across scenarios?is_random
The item in a slot, and the slot of an itemitem_at slot_of
Follow up a submitted jobjob_delete job_log job_result job_status
A table of data indexed by decisionslookup_table [.quicopt_table
Set the objectivemaximize minimize
Create an empty modelmodel
Declare decision variablesadd_var bin_var int_var num_var
A random variable with a distribution, for building a program by handparametric
The part of an item, and the size of a partpart_of size_of
Divide items into groups as a decisionadd_part_var part_var
A partition, for building a program by handpartition_decl
Declare an ordering as a decisionadd_perm_var perm_var
A permutation, for building a program by handpermutation_decl
Require one item to come before anotherprecede
The probability that a comparison holdsprob
A model as plain dataprogram
Declare a random variableadd_rand_var rand_var
Check a solution on new scenariosresample
The largest, the smallest and a quantile over the scenariosscenario_max scenario_min scenario_quantile
Give a random variable its distributionset_distribution
Use observed data as a model's uncertaintyset_empirical
Set how many scenarios are drawn, and from which seedset_scenarios
Start the next search from a known solutionset_start
Solve a modelsolve.quicopt_model solve_model
Optimization under uncertaintystochastic
Solve a model without waitingsubmit
Sums, products, maxima and minimamax min prod sum summaries
The variance and the standard deviation over the scenariosstd_dev variance
The bytes sent to the servicewire