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juj
RectangleBinPack
C++2013–2024
juj / RectangleBinPack

RectangleBinPack

Source code for performing 2d rectangular bin packing.

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2Distinct people
2Mentions
0Explicit recommenders
999GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Source code for performing 2d rectangular bin packing.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year2 dated mentions

Observed mentions: 2013-04-05 22:14:25 UTC to 2024-11-18 19:19:26 UTC.

012013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20132014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC110
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC000
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC000
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

2 sources
andrewtbham·Apr 5, 2013Submission

ASk HN: How do I solve 2d bin packing problem if I can change the bin size?

I have been tasked with optimizing a manufacturing process. It is a non-trivial, NP hard problem. The problem is similar to the 2d bin packing problem, but we are trying to optimize the size of the bins. Small rectangular shapes must be packed into larger rectangles in an optimal way. There are nesting algorithms to do this optimization where the large rectangle dimensions are inputs. However, we want to optimize the dimensions of the large rectangles. The inputs are: -A list of unique small rectangles. The list includes the dimensions of the small rectangles, a number that represents the rectangle’s frequency of usage relative to the other small rectangles, and the orientation (whether or not it can be rotated 90 degrees) -The maximum number of large rectangle dimensions. And the minimum and maximum dimensions of the large rectangl
Read the rest
es. The output is an optimized list of large rectangle dimensions. One way to prove the validity of the result is by creating a nest of the small rectangles within the large rectangles. Here is a paper and an open source project that provides a solution to the 2d bin packing problem that we are currently using to nest. We are using the Maximal Rectangle algorithm and we vary the heuristics (typically bottom left or contact point heuristics). http://clb.demon.fi/files/RectangleBinPack.pdf https://github.com/juj/RectangleBinPack How do I solve this problem?
1 points · Open discussion

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