https://github.com/delta1epsilon/BoxPacking

R package for solving three-dimensional bin packing problem
https://github.com/delta1epsilon/BoxPacking

3d-bin-packing-problem genetic-algorithm packing-algorithm r

Last synced: 3 months ago
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R package for solving three-dimensional bin packing problem

• Host: GitHub
• URL: https://github.com/delta1epsilon/BoxPacking
• Owner: delta1epsilon
• Created: 2016-09-23T18:30:50.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2017-04-20T07:18:36.000Z (over 7 years ago)
• Last Synced: 2024-05-19T23:37:30.626Z (6 months ago)
• Topics: 3d-bin-packing-problem, genetic-algorithm, packing-algorithm, r
• Language: R
• Homepage: https://delta1epsilon.github.io/2016/3D-bin-packing-problem-in-R/
• Size: 1000 KB
• Stars: 63
• Watchers: 4
• Forks: 22
• Open Issues: 3
• Metadata Files:
  • Readme: README.md

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README

        
# BoxPacking: R package for solving three-dimensional bin packing problem

## Problem description

In the bin packing problem, the task is to select one or more bins from a set of available bins to pack three dimensional, rectangular boxes such that the usage of the bin space is maximized. [Read more about the problem.](https://en.wikipedia.org/wiki/Bin_packing_problem)

## Algorithm

The package uses [Genetic algorithm for the three-dimensional bin packing problem with heterogeneous bins](https://www.researchgate.net/publication/273121476_A_genetic_algorithm_for_the_three-dimensional_bin_packing_problem_with_heterogeneous_bins).

You can read more about the algorithm in my [blog post](https://delta1epsilon.github.io/2016/3D-bin-packing-problem-in-R/). 

## Install

```

devtools::install_github('delta1epsilon/BoxPacking')

```

## Example

Consider an example where 20 boxes of different sizes are going to be packed into containers 2x2x2.

```

library(BoxPacking)

# create containers

containers <- list()

n_containers <- 4

for (i in 1:n_containers) {

    containers <- c(containers,

                    Container(length = 2, height = 2, width = 2)

                    )

}

# create boxes

boxes <- list()

n_boxes <- 20

for (i in 1:n_boxes) {

    length <- sample(c(0.4, 0.5, 1), 1)

    height <- sample(c(0.4, 0.5, 1), 1)

    width <- sample(c(0.4, 0.5, 1), 1)

    boxes <- c(boxes,

               Box(length = length, height = height, width = width)

               )

}

# Box Packing

solution <-

    PerformBoxPacking(containers = containers,

                      boxes = boxes,

                      n_iter = 4,

                      population_size = 20,

                      elitism_size = 5,

                      crossover_prob = 0.5,

                      mutation_prob = 0.5,

                      verbose = TRUE,

                      plotSolution = TRUE

                      )

```

![](giphy.gif)