Name
Abstract | ||
|---|---|---|
Summary Recursive linear programming is defined by a sequence of linear programming problems in which a recursive relation is built into the system through either the coefficients of the objective function, the constraint matrix, or the right-hand side parameters. Here we consider the case where the right-hand side parameters are subject to a recursive time relation indicating how current period plans are related to past expectations and performance. Our object here is twofold: first, to analyze the stability properties of a linear recursive programming (LRP) model and second, to indicate some basic extensions of the LRP in the light of what is generally called ‘the active approach’ of stochastic linear programming (SLP). Some simple theorems are developed in this connection and this is followed by a brief discussion of the possible lines of empirical applications. |
Year | DOI | Venue |
|---|---|---|
1966 | 10.1007/BF01918280 | Unternehmensforschung |
Field | DocType | Volume |
Linear-fractional programming,Mathematical optimization,Stochastic linear programming,Recursive language,Linear programming,μ operator,Recursion,Constraint matrix,Mathematics,Recursive programming | Journal | 10 |
Issue | Citations | PageRank |
1 | 1 | 0.53 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jati K. Sengupta | 1 | 72 | 60.40 |
| Gerhard Tintner | 2 | 3 | 1.54 |