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Knapsack: minor correction to docs; update docstrings

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Alinson S. Xavier
2020-01-31 10:34:04 -06:00
parent 7b4437f2ab
commit 46e19eed1b
2 changed files with 4 additions and 2 deletions
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2
docs/problems.md
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@@ -93,7 +93,7 @@ If `fix_w=True` is provided, then $w_{ij}$ are kept the same in all generated in
If a probability distribution `w_jitter` is provided, then item weights will be set to $w_{ij} + \gamma_{ij}$ where $\gamma_{ij}$ is sampled from `w_jitter`. When combined with `fix_w=True`, this argument may be used to generate instances where the weight of each item is roughly the same, but not exactly identical, across all instances. The prices of the items and the capacities of the knapsacks will be calculated as above, but using these perturbed weights instead. If a probability distribution `w_jitter` is provided, then item weights will be set to $w_{ij} + \gamma_{ij}$ where $\gamma_{ij}$ is sampled from `w_jitter`. When combined with `fix_w=True`, this argument may be used to generate instances where the weight of each item is roughly the same, but not exactly identical, across all instances. The prices of the items and the capacities of the knapsacks will be calculated as above, but using these perturbed weights instead.
By default, all generated prices, weights and capacities are rounded to the nearest number. If `round=False` is provided, this rounding will be disabled. By default, all generated prices, weights and capacities are rounded to the nearest integer number. If `round=False` is provided, this rounding will be disabled.
!!! note "References" !!! note "References"
* Freville, Arnaud, and Gérard Plateau. *An efficient preprocessing procedure for the multidimensional 0–1 knapsack problem.* Discrete applied mathematics 49.1-3 (1994): 189-212. * Freville, Arnaud, and Gérard Plateau. *An efficient preprocessing procedure for the multidimensional 0–1 knapsack problem.* Discrete applied mathematics 49.1-3 (1994): 189-212.

4
miplearn/problems/knapsack.py
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@@ -130,7 +130,6 @@ class MultiKnapsackGenerator:
from w[i,j], as long as u and K are not constants, the generated instances will still not from w[i,j], as long as u and K are not constants, the generated instances will still not
be completely identical. be completely identical.
If a probability distribution w_jitter is provided, then item weights will be set to If a probability distribution w_jitter is provided, then item weights will be set to
w[i,j] + gamma[i,j] where gamma[i,j] is sampled from w_jitter. When combined with w[i,j] + gamma[i,j] where gamma[i,j] is sampled from w_jitter. When combined with
fix_w=True, this argument may be used to generate instances where the weight of each item fix_w=True, this argument may be used to generate instances where the weight of each item
@@ -138,6 +137,9 @@ class MultiKnapsackGenerator:
items and the capacities of the knapsacks will be calculated as above, but using these items and the capacities of the knapsacks will be calculated as above, but using these
perturbed weights instead. perturbed weights instead.
By default, all generated prices, weights and capacities are rounded to the nearest integer
number. If `round=False` is provided, this rounding will be disabled.
Parameters Parameters
---------- ----------
n: rv_discrete n: rv_discrete