Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.08441 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911259628142592 |
|---|---|
| author | Schaefer, Elizabeth J. Schaefer, Andrew J. |
| author_facet | Schaefer, Elizabeth J. Schaefer, Andrew J. |
| contents | We give two graph-theoretic models and a mixed-integer program to calculate the maximum achievable score in the popular board game "Ticket to Ride." In Ticket to Ride, players compete to claim railway routes on a map, with points awarded based on the length of each route and the successful completion of destination tickets connecting specific city pairs. Each player has 45 train cars available, and each route can be chosen by only one player. Using the mixed-integer programming model, we examine the optimal solution with the 45 allocatable train cars, leading to an optimal score of 285 points. We also calculate the optimal solutions for up to 50 train cars. We determine the most frequently chosen tickets and routes over these 50 instances, giving insight into how optimization might be used to balance games. In particular, we identify several instances in which the point values can be adjusted to better balance the game. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_08441 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Maximizing the Score in "Ticket to Ride" Schaefer, Elizabeth J. Schaefer, Andrew J. Optimization and Control We give two graph-theoretic models and a mixed-integer program to calculate the maximum achievable score in the popular board game "Ticket to Ride." In Ticket to Ride, players compete to claim railway routes on a map, with points awarded based on the length of each route and the successful completion of destination tickets connecting specific city pairs. Each player has 45 train cars available, and each route can be chosen by only one player. Using the mixed-integer programming model, we examine the optimal solution with the 45 allocatable train cars, leading to an optimal score of 285 points. We also calculate the optimal solutions for up to 50 train cars. We determine the most frequently chosen tickets and routes over these 50 instances, giving insight into how optimization might be used to balance games. In particular, we identify several instances in which the point values can be adjusted to better balance the game. |
| title | Maximizing the Score in "Ticket to Ride" |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2511.08441 |