Showing papers on "Goal programming published in 1971"

Decision analysis through goal programming

Abstract: In recent years, decision making based on systematic analysis has been greatly emphasized. Yet, decision analysis is often carried out without analyzing the limitations of certain quantitative techniques. This paper presents the concept, solution method, and application potential of goal programming which eliminates many limitations of conventional linear optimization models.

Multi-Level Models for Career Management and Resource Planning.

Abstract: : The OCMM models for manpower planning were initially formulated in terms of a goal-programming, Markoff process combination with the latter embedded in the former. This subsequently admitted to a further extension in which the Markovian elements were reformulated so that they could be submitted to chance-constrained programming use and interpretations. They made it possible to plan for personnel recruitment, training, re-training and stochastically determined transfers, so that selected constraint stipulations would be honored with prescribed probabilities in any set of differing time intervals for which such constraints might be imposed. Here, a further extension is made: An input-output (Leontief) analysis of an often one-period variety is embedded in a goal programming formulation. Applications to manpower planning and resource allocation are examined for their support as well as their direct activity implications. A further development via chance-constrained programming in a different direction is then provided which comprehends elements in the objective, as well as the constraints, in a formulation that can then be interpreted as an extension of goal programming to such probabilistic considerations. (Author)

Mathematical Models for Manpower and Personnel Planning.

Abstract: : Current work in mathematical modeling for manpower planning and personnel administration is reviewed with special reference to selected cases in the U S Navy This includes (1) assignment models and their dynamic extensions (2) stochastic models with special reference to Markoff processes, including OCMM's goal programming extensions, (3) input-output and activity analysis models and (4) combinations and extensions, with mathematical programming relations delineated Evaluations of existing developments are also delineated along with possible paths for future development strategies Potentials for science as well as management are explored (Author)