Online Knapsack Revisited
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10331546" target="_blank" >RIV/00216208:11320/16:10331546 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1007/s00224-014-9566-4" target="_blank" >http://dx.doi.org/10.1007/s00224-014-9566-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00224-014-9566-4" target="_blank" >10.1007/s00224-014-9566-4</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Online Knapsack Revisited
Popis výsledku v původním jazyce
We investigate the online variant of the (Multiple) Knapsack Problem: an algorithm is to pack items, of arbitrary sizes and profits, in k knapsacks (bins) without exceeding the capacity of any bin. We study two objective functions: the sum and the maximum of profits over all bins. With either objective, our problem statement captures and generalizes previously studied problems, e.g. Dual Bin Packing [1, 6] in case of the sum and Removable Knapsack [10, 11] in case of the maximum. Following previous studies, we consider two variants, depending on whether the algorithm is allowed to remove items (forever) from its bins or not, and two special cases where the profit of an item is a function of its size, in addition to the general setting. We study both deterministic and randomized algorithms; for the latter, we consider both the oblivious and the adaptive adversary model. We classify each variant as either admitting O(1)-competitive algorithms or not. We develop simple O(1)-competitive algorithms for some cases of the max-objective variant believed to be intrac because only 1-bin deterministic algorithms were considered before.
Název v anglickém jazyce
Online Knapsack Revisited
Popis výsledku anglicky
We investigate the online variant of the (Multiple) Knapsack Problem: an algorithm is to pack items, of arbitrary sizes and profits, in k knapsacks (bins) without exceeding the capacity of any bin. We study two objective functions: the sum and the maximum of profits over all bins. With either objective, our problem statement captures and generalizes previously studied problems, e.g. Dual Bin Packing [1, 6] in case of the sum and Removable Knapsack [10, 11] in case of the maximum. Following previous studies, we consider two variants, depending on whether the algorithm is allowed to remove items (forever) from its bins or not, and two special cases where the profit of an item is a function of its size, in addition to the general setting. We study both deterministic and randomized algorithms; for the latter, we consider both the oblivious and the adaptive adversary model. We classify each variant as either admitting O(1)-competitive algorithms or not. We develop simple O(1)-competitive algorithms for some cases of the max-objective variant believed to be intrac because only 1-bin deterministic algorithms were considered before.
Klasifikace
Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
IN - Informatika
OECD FORD obor
—
Návaznosti výsledku
Projekt
<a href="/cs/project/GA14-10003S" target="_blank" >GA14-10003S: Omezené typy výpočtů: algoritmy, modely, složitost</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2016
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Theory of Computing Systems
ISSN
1432-4350
e-ISSN
—
Svazek periodika
58
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
DE - Spolková republika Německo
Počet stran výsledku
38
Strana od-do
153-190
Kód UT WoS článku
000367607000009
EID výsledku v databázi Scopus
2-s2.0-84952975971