Arc reduction and path preference in stochastic acyclic networks

Article Abstract:

A heuristic for calculating the path for maximizing the expected utility of a stochastic acyclic network is presented. The heuristic reduces computational complexity by reducing the size of the network. The method obtains a group of attractive solutions by combining Monte Carlo simulation and shortest path techniques. The emphasis is on shortest route problems in which outcomes are measured by a general, nonlinear utility function. The global optimum is found by the enumeration of all feasible paths. A reduction algorithm based on stochastic dominance was developed to speed up calculations and evaluated using Monte Carlo simulation. Some 70 test problems involving 20 to 60 nodes were generated randomly and analyzed. The results suggested that the heuristic resulted in considerable computational savings as the network increased in size, and that the quality of the reduced network solutions was superior to the quality of those derived from the original formula.

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Parallel funding of R & D tasks with probabilistic outcomes

Article Abstract:

Obtaining funding for repetitive projects associated with single research and development programs is a difficult task. Optimal funding for each phase of such a research project is modeled as a heuristic using dynamic programming methods and simulation. The source of the funding problem is stated as a probabilistic network, after overall project results have been measured using utility functions. The model developed is applied successfully to research programs involving the development of photovoltaic modular cells.

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Flight scheduling and maintenance base planning

Article Abstract:

Airlines are working on rationalizing their maintenance operations as a source of savings. Federal regulations and in-house safety policies limit the amount of cost savings that can be effected by improving productivity and scheduling. A multicommodity flow network model derived from American Airlines' Boeing 727 fleet data provides management with the ability to schedule and locate maintenance service stations in order to maximize maintenance in accordance to cyclical demand.

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