Using Probabilistic Information in Solving Resource Allocation Problems for a Decentralized Firm
STANFORD UNIV CA DEPT OF OPERATIONS RESEARCH
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This paper formulates a general linear programming problem for a multidivision firm where headquarters possesses probabilistic information regarding each divisions opportunities. It is assumed that headquarters is willing to risk implementing a plan which may not be optimal in order to avoid collecting detailed information from the divisions. Headquarters willingness to take a risk is modelled via the use of chance constraints. An iterative procedure which is derived from the Dantzig-Wolfe decomposition principle is presented which allows headquarters to combine deterministic information from the divisions with its stochastic information to arrive at a resource allocation plan. Characteristics of the resulting plan are discussed relative to headquarters risk attitude and its probabilistic information. The procedure is adapted to situations where the size of headquarters programming problem has to be reduced.
- Economics and Cost Analysis
- Operations Research