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Decision Support for Planning and Resource Allocation in Hierarchical Organizations

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Planning in hierarchical organizations frequently involves interpreting objectives assigned by a superordinate, developing objectives to assign to subordinates, and allocating resources to subordinates for the accomplishment of their objectives. The planning problem is to develop a program of objectives that is feasible within the resource constraints, and which provides the best possible contribution to the superordinate's plan. Resource allocation is computation intensive and is a prime candidate for mathematical programming decision support. The principal difficulty in applying mathematical programming techniques is the lack of a suitable structure defining the relationship between resource allocations and contribution to the overarching objectives of the superordinate. A decision support methodology for planning and resource allocation in hierarchical organizations is presented. The methodology employs a goal-reduction model based on logical principles for the decomposition of objectives. The model has a natural mathematical interpretation of the composition effects of accomplishing subgoals. The same principles used in reducing the abstraction of the objectives are used in aggregating the contributions of allocated resources to the objectives. The notion of archetype objectives used as intermediate steps in goal reduction is developed. An interactive optimization procedure is described in which an optimization algorithm is used to develop trial solutions, and in which user preferences and priorities are elicited in the context of the trial solutions. The goal structure is the basis for the optimization function and the interactions with the user. Fire support planning in combined arms operations is used to illustrate the approach.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics  (Volume:16 ,  Issue: 6 )