There is a need to develop user-oriented math programming techniques for resolution of decision problems in which several objectives must be considered. One approach, the Geoffrion-Dyer-Feinberg algorithm, allows interaction between the computer and the decision maker during the solution process. The interactive approach is adopted in this paper. However, our approach focuses on reducing the feasible region of the decision space rather than improving the stored image of the overall preference function. In so doing, the problem is reduced to a series of pairwise tradeoffs between the objectives. This obviates the need for any type of choice among vectors on the part of the decision maker and stays reasonably within his capability to supply necessary information for problem solution.
A decision rule for real-time dispatching of parts, each of which may have alternative processing possibilities, has been developed and tested in a simulated flexible manufacturing system. A part, upon completion of an operation, is not routed to a specific machine,but is,ineffect, sent to a generalqueue.Thus, a machine has a global option lorchoosing parts whichin turn may be processed on alternative machines. For effective use of the system's routeing flexibility under these circumstances,the machine needs an intelligent part-selection strategy (rather than shallow heuristicsrepresented by the conventional dispatching rules)that takes into account the current state and trends of the system. The proposed intelligent reasoning procedure has beenfound to achievebetter shop performancethan some of the popular dispatching rules,the improved performance beingdue to the ability to respond to changing circumstances.
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