STOCHASTIC ONLINE KNAPSACK-PROBLEMS

被引：90
|
作者：
MARCHETTISPACCAMELA, A
VERCELLIS, C
机构：
[1] POLITECN MILAN,DIPARTIMENTO ECON & PROD,I-20133 MILAN,ITALY
[2] UNIV ROMA LA SAPIENZA,DIPARTIMENTO INFORMAT & SISTEMIST,ROME,ITALY
来源：
MATHEMATICAL PROGRAMMING | 1995年 / 68卷 / 01期
关键词：
KNAPSACK PROBLEMS; ONLINE ALGORITHMS; STOCHASTIC INTEGER PROGRAMMING;
D O I：
10.1007/BF01585758
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Different classes of on-line algorithms are developed and analyzed for the solution of {0, 1} and relaxed stochastic knapsack problems, in which both profit and size coefficients are random variables. In particular, a linear time on-line algorithm is proposed for which the expected difference between the optimum and the approximate solution value is O(log(3/2) n). An Omega(1) lower bound on the expected difference between the optimum and the solution found by any on-line algorithm is also shown to hold.
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页码：73 / 104
页数：32
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