TY - GEN
T1 - Knapsack secretary through boosting
AU - Abels, Andreas
AU - Ladewig, Leon
AU - Schewior, Kevin
AU - Stinzendörfer, Moritz
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - We revisit the knapsack-secretary problem (Babaioff et al.; APPROX 2007), a generalization of the classic secretary problem in which items have different sizes and multiple items may be selected if their total size does not exceed the capacity B of a knapsack. Previous works show competitive ratios of 1/(10e) (Babaioff et al.), 1/8.06 (Kesselheim et al.; STOC 2014), and 1/6.65 (Albers, Khan, and Ladewig; APPROX 2019) for the general problem but no definitive answers for the achievable competitive ratio; the best known impossibility remains 1/e as inherited from the classic secretary problem. In an effort to make more qualitative progress, we take an orthogonal approach and give definitive answers for special cases. Our main result is on the 1-2-knapsack secretary problem, the special case in which B= 2 and all items have sizes 1 or 2, arguably the simplest meaningful generalization of the secretary problem towards the knapsack secretary problem. Our algorithm is simple: It boosts the value of size-1 items by a factor α> 1 and then uses the size-oblivious approach by Albers, Khan, and Ladewig. We show by a nontrivial analysis that this algorithm achieves a competitive ratio of 1/e if and only if 1.40 ≲ α≤ e/ (e- 1 ) ≈ 1.58. Towards understanding the general case, we then consider the case when sizes are 1 and B, and B is large. While it remains unclear if 1/e can be achieved in that case, we show that algorithms based only on the relative ranks of the item values can achieve precisely a competitive ratio of 1 / (e+ 1 ). To show the impossibility, we use a non-trivial generalization of the factor-revealing linear program for the secretary problem (Buchbinder, Jain, and Singh; IPCO 2010).
AB - We revisit the knapsack-secretary problem (Babaioff et al.; APPROX 2007), a generalization of the classic secretary problem in which items have different sizes and multiple items may be selected if their total size does not exceed the capacity B of a knapsack. Previous works show competitive ratios of 1/(10e) (Babaioff et al.), 1/8.06 (Kesselheim et al.; STOC 2014), and 1/6.65 (Albers, Khan, and Ladewig; APPROX 2019) for the general problem but no definitive answers for the achievable competitive ratio; the best known impossibility remains 1/e as inherited from the classic secretary problem. In an effort to make more qualitative progress, we take an orthogonal approach and give definitive answers for special cases. Our main result is on the 1-2-knapsack secretary problem, the special case in which B= 2 and all items have sizes 1 or 2, arguably the simplest meaningful generalization of the secretary problem towards the knapsack secretary problem. Our algorithm is simple: It boosts the value of size-1 items by a factor α> 1 and then uses the size-oblivious approach by Albers, Khan, and Ladewig. We show by a nontrivial analysis that this algorithm achieves a competitive ratio of 1/e if and only if 1.40 ≲ α≤ e/ (e- 1 ) ≈ 1.58. Towards understanding the general case, we then consider the case when sizes are 1 and B, and B is large. While it remains unclear if 1/e can be achieved in that case, we show that algorithms based only on the relative ranks of the item values can achieve precisely a competitive ratio of 1 / (e+ 1 ). To show the impossibility, we use a non-trivial generalization of the factor-revealing linear program for the secretary problem (Buchbinder, Jain, and Singh; IPCO 2010).
U2 - 10.1007/978-3-031-18367-6_4
DO - 10.1007/978-3-031-18367-6_4
M3 - Article in proceedings
AN - SCOPUS:85142729750
SN - 9783031183669
T3 - Lecture Notes in Computer Science
SP - 61
EP - 81
BT - Approximation and Online Algorithms - 20th International Workshop, WAOA 2022, Proceedings
A2 - Chalermsook, Parinya
A2 - Laekhanukit, Bundit
PB - Springer Science+Business Media
T2 - 20th International Workshop on Approximation and Online Algorithms, WAOA 2022
Y2 - 8 September 2022 through 9 September 2022
ER -