README.Rmd

---
output: github_document
---

# GroupAssignment

## Documentation

## Installation

```r
devtools::install_github("hkunda/GroupAssignment")
```

### Inputs

@rankings [NumericMatrix]: a matrix of rankings for each student. The ith row corresponds to student i,
and the jth column corresponds to the student in position j on any student's ranking list. If there are
N students, then each student should have an ID in the range [1,N], which is used both as the row index
(to refer to a student's rankings) and entries of the matrix. For example, if rankings[i,j] = k, then
student i has placed student k in position j on i's ranking.

@students [int]: the number of students. This should be equal to the number of rows in @rankings.

@leaders [int]: the number of leaders to pick; equivalently, the number of groups to form.

@minGroupSize [int]: the minimum number of students in a group. NOTE: this value does include the group
leader. So if minGroupSize = 4, then every group must consist of 1 leader and at least 3 other students.

@maxGroupSize [int]: the maximum number of students in a group. NOTE: this value does include the group
leader. So if maxGroupSize = 6, then every group must consist of 1 leader and at most 5 other students.

### Outputs

Returns a NumericVector of length students+1. The ith element of the output is the id of the student
leading the group that student i is in (for 0 <= i <= N). The N+1st element of the output is the total
cost of the optimal matching.

### Examples

```{r Simple example}
library(igraph)
library(GroupAssignment)

set.seed(712)

x <- sample_smallworld(1, 20, 4, .1)
d <- distances(x) + 1
d <- max(d) - d + 1

ans <- optimalAssignment(d, leaders = 3, minGroupSize = 2, maxGroupSize = 10)
ans
```