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 What is the best strategy for a purchaser choosing suppliers, when the quality of each is described by a distribution function? Should a purchaser deal with a new supplier, without a history, who may be better than existing suppliers? The authors’ approach is based on Gittins indices [1], but is generalized to stochastic buying intervals, different supplier prices, and different size purchases.
A helpful example demonstrates the approach. When a new supplier appears, Gittins indices cannot be calculated, because the history of the supplier is not known. Several strategies are suggested and simulated. The trade-off is between using present information (exploitation), and learning about new suppliers (exploration). One strategy is to calculate the index of the new supplier (using a short history implying a high index) from the average performance of the other suppliers. Another strategy is to select new suppliers randomly. A third strategy is to always choose a new supplier if one appears, and a final strategy is to never choose a new supplier.
The results of the simulations are reasonable. With one known supplier, and one new supplier, it is best to explore and try the new supplier. With four or five known suppliers, it is best to ignore new suppliers. With two known suppliers, it is best to assign the new supplier the average performance. The paper is wordy, but effectively demonstrates how to apply the approach to particular problems.
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Reviewer:
B. Hazeltine
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Review #: CR130726
(0508-0948) |
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1) |
Gittins, J.C. Multi-armed bandit allocation indices. Wiley, New York, NY, 1989. |
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