A branch and bound method for stochastic integer problems under probabilistic constraints

被引：60

作者：

Beraldi, P

Ruszczynski, A

机构：

[1] Rutgers State Univ, Dept Management Sci & Informat Syst, Piscataway, NJ 08854 USA

[2] Rutgers State Univ, RUTCOR, Piscataway, NJ 08854 USA

[3] Univ Calabria, Dipartimento Elettron Informat & Sistemist, I-87036 Arcavacata Di Rende, Italy

来源：

OPTIMIZATION METHODS & SOFTWARE | 2002年 / 17卷 / 03期

关键词：

stochastic integer programming; probabilistic programming; branch and bound;

D O I：

10.1080/1055678021000033937

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Stochastic integer programming problems under probabilistic constraints are considered. Deterministic equivalent formulations of the original problem are obtained by using p -efficient points of the distribution function of the right hand side vector. A branch and bound solution method is proposed based on a partial enumeration of the set of these points. The numerical experience with the probabilistic lot-sizing problem shows the potential of the solution approach and the efficiency of the algorithms implemented.

引用

页码：359 / 382

页数：24

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