Abstract

Arachne provides an excellent example of the success that can be derived from an effective integration of expert systems and optimization techniques. Automating IOF planning at NYNEX was an extremely challenging problem involving conflicting constraints: (i) the IOF network planning problem is quite complex, and (ii) the size of NYNEX s IOF network is quite large. In Arachne, we resolve these conflicting constraints by decomposing the planning task in such a way that only two types of subtask remain: (i) subtasks in which the size of the data is large, and the equipment cost of decisions small, an (ii) subtasks in which the data size is small and the equipment cost of decisions high. We apply heuristics to the former types of subtasks and optimization techniques to the latter. Combining heuristics and optimization techniques in this way provides a very good solution that optimizes the IOF network where capital investment is greatest. Copyright

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