set_runs_manual: Define a manual multi-objective run design

In multiscape: Multi-Action, Multi-Objective Spatial Planning

Define a manual multi-objective run design

Description

Create an explicit run-design specification in which each row defines one multi-objective optimization run.

set_runs_manual() is used when exact objective weights or epsilon levels should be supplied by the user instead of being generated automatically with set_runs_grid.

Usage

set_runs_manual(x)

Arguments

x	A non-empty data.frame with one row per optimization run. Run-design columns must be named using the weight_<alias> or eps_<alias> convention.

Details

The input must be a non-empty data.frame with one row per requested optimization run.

Weighted-sum columns must follow the convention:

weight_<alias>

Epsilon-constraint and AUGMECON columns must follow the convention:

eps_<alias>

A manual design must contain at least one column beginning with weight_ or eps_. Mixing both column families in the same design is not allowed.

All run-design columns must be numeric, finite, and free of missing values. Weight columns must contain non-negative values, and each weighted-sum row must assign a strictly positive total weight.

This function performs method-independent structural validation. Method-specific validation is performed later by the corresponding set_method_*() function. This includes checking:

• that all required objective aliases are represented;

• that no unknown objective columns are supplied;

• that epsilon columns correspond only to secondary objectives;

• and that the supplied design is compatible with the selected method.

Therefore, an object may be structurally valid for set_runs_manual() but rejected later by set_method_weighted_sum, set_method_epsilon_constraint, or set_method_augmecon.

Value

An object of class RunManual and RunDesign containing the validated run table.

See Also

set_runs_grid, set_method_weighted_sum, set_method_epsilon_constraint, set_method_augmecon

Examples

weighted_runs <- set_runs_manual(
  data.frame(
    weight_cost = c(1.0, 0.5, 0.0),
    weight_benefit = c(0.0, 0.5, 1.0)
  )
)

epsilon_runs <- set_runs_manual(
  data.frame(
    eps_benefit = c(2, 4, 6, 8)
  )
)

weighted_runs
epsilon_runs

multiscape documentation built on Oct. 12, 2026, 5:08 p.m.