Conduct Multi-Objective Optimization on An EnergyPlus Model

GAOptimJob class provides a prototype of conducting single- or multi- objective(s) optimizations on an EnergyPlus model using Genetic Algorithm

Details

The basic workflow is basically:

Author

Hongyuan Jia

Super classes

eplusr::EplusGroupJob -> eplusr::ParametricJob -> GAOptimJob

Methods

Public methods

• GAOptimJob$new()

• GAOptimJob$param()

• GAOptimJob$apply_measure()

• GAOptimJob$objective()

• GAOptimJob$recombinator()

• GAOptimJob$mutator()

• GAOptimJob$selector()

• GAOptimJob$terminator()

• GAOptimJob$validate()

• GAOptimJob$run()

• GAOptimJob$best_set()

• GAOptimJob$pareto_set()

• GAOptimJob$population()

• GAOptimJob$print()

Inherited methods

• eplusr::EplusGroupJob$errors()

• eplusr::EplusGroupJob$kill()

• eplusr::EplusGroupJob$list_table()

• eplusr::EplusGroupJob$locate_output()

• eplusr::EplusGroupJob$output_dir()

• eplusr::EplusGroupJob$read_mdd()

• eplusr::EplusGroupJob$read_rdd()

• eplusr::EplusGroupJob$read_table()

• eplusr::EplusGroupJob$report_data()

• eplusr::EplusGroupJob$report_data_dict()

• eplusr::EplusGroupJob$status()

• eplusr::EplusGroupJob$tabular_data()

• eplusr::ParametricJob$models()

• eplusr::ParametricJob$save()

• eplusr::ParametricJob$seed()

• eplusr::ParametricJob$version()

• eplusr::ParametricJob$weather()

---

Method new()

Create a GAOptimJob object

Usage

GAOptimJob$new(idf, epw)

Arguments

idf

A path to an local EnergyPlus IDF file or an eplusr::Idf object.

epw

A path to an local EnergyPlus EPW file or an eplusr::Epw object.

Returns

A GAOptimJob object.

Examples

\dontrun{
if (eplusr::is_avail_eplus(8.8)) {
idf_name <- "1ZoneUncontrolled.idf"
epw_name <-  "USA_CA_San.Francisco.Intl.AP.724940_TMY3.epw"

idf_path <- file.path(eplusr::eplus_config(8.8)$dir, "ExampleFiles", idf_name)
epw_path <- file.path(eplusr::eplus_config(8.8)$dir, "WeatherData", epw_name)

# create from local files
GAOptimJob$new(idf_path, epw_path)

# create from an Idf and an Epw object
opt <- GAOptimJob$new(eplusr::read_idf(idf_path), eplusr::read_epw(epw_path))
}
}

---

Method param()

Usage

GAOptimJob$param(..., .names = NULL)

---

Method apply_measure()

Usage

GAOptimJob$apply_measure(measure, ..., .names = NULL)

---

Method objective()

Usage

GAOptimJob$objective(..., .n = NULL, .dir = "min")

---

Method recombinator()

Usage

GAOptimJob$recombinator(
...,
.float = setwith(ecr::recSBX, eta = 15, p = 0.7),
.integer = setwith(recPCrossover, p = 0.7),
.choice = setwith(recPCrossover, p = 0.7)
)

---

Method mutator()

Usage

GAOptimJob$mutator(
...,
.float = setwith(ecr::mutPolynomial, eta = 25, p = 0.1),
.integer = mutRandomChoice,
.choice = mutRandomChoice
)

---

Method selector()

Usage

GAOptimJob$selector(
parent = ecr::selSimple,
survival = ecr::selNondom,
strategy = "plus"
)

---

Method terminator()

Usage

GAOptimJob$terminator(
fun = NULL,
name,
message,
max_gen = NULL,
max_eval = NULL,
max_time = NULL
)

---

Method validate()

Usage

GAOptimJob$validate(param = NULL, ddy_only = TRUE, verbose = TRUE)

---

Method run()

Usage

GAOptimJob$run(
mu = 20L,
p_recomb = 0.7,
p_mut = 0.1,
dir = NULL,
wait = TRUE,
parallel = TRUE
)

---

Method best_set()

Usage

GAOptimJob$best_set(unique = TRUE)

---

Method pareto_set()

Usage

GAOptimJob$pareto_set(unique = TRUE)

---

Method population()

Usage

GAOptimJob$population()

---

Method print()

Usage

GAOptimJob$print()

Examples

## ------------------------------------------------
## Method `GAOptimJob$new`
## ------------------------------------------------

# \dontrun{
if (eplusr::is_avail_eplus(8.8)) {
idf_name <- "1ZoneUncontrolled.idf"
epw_name <-  "USA_CA_San.Francisco.Intl.AP.724940_TMY3.epw"

idf_path <- file.path(eplusr::eplus_config(8.8)$dir, "ExampleFiles", idf_name)
epw_path <- file.path(eplusr::eplus_config(8.8)$dir, "WeatherData", epw_name)

# create from local files
GAOptimJob$new(idf_path, epw_path)

# create from an Idf and an Epw object
opt <- GAOptimJob$new(eplusr::read_idf(idf_path), eplusr::read_epw(epw_path))
}
# }