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Single entry point that replaces the original main.R script.

Usage

run_momst(
  instance = NULL,
  instance_file = NULL,
  n = 10L,
  num_obj = 2L,
  variant = c("base", "PR", "PLS", "TS"),
  iterations = 10L,
  pop_size = 50L,
  tour_size = 2L,
  cross_rate = 0.8,
  mut_rate = 0.05,
  max_generations = 100L,
  convergence_window = 10L,
  range_a = c(10, 100),
  range_b = c(10, 50),
  range_c = c(30, 200),
  save_dir = NULL,
  verbose = TRUE,
  seed = NULL
)

Arguments

instance

Optional data.frame.

instance_file

Optional path.

n

Integer.

num_obj

Integer in {2, 3}.

variant

One of "base", "PR", "PLS", "TS".

iterations

Integer or two-length integer c(min_iter, max_iter).

pop_size

Integer (must be even).

tour_size

Integer.

cross_rate

Numeric in \[0, 1\].

mut_rate

Numeric in \[0, 1\].

max_generations

Integer.

convergence_window

Integer.

range_a, range_b, range_c

Weight ranges for instance generation.

save_dir

Optional directory for per-iteration result files.

verbose

Logical.

seed

Optional integer.

Value

Invisible list with the solution data.

References

Parraga-Alava, J., Inostroza-Ponta, M., & Dorn, M. (2017). Using local search strategies to improve the performance of NSGA-II for the Multi-Criteria Minimum Spanning Tree problem. In 2017 IEEE Congress on Evolutionary Computation (CEC) (pp. 1818-1825). IEEE. doi:10.1109/CEC.2017.7969432

Examples

if (FALSE) { # \dontrun{
res <- run_momst(n = 10, num_obj = 2, iterations = 3,
                 pop_size = 20, max_generations = 30,
                 variant = "base", seed = 1)
head(res$global_pareto)
} # }