Consider a setting with multiple demand classes that are served by a set of resources. When each resource is limited to serving only one demand class, we can often have a situation where some resources are under-utilized and idle, while others are over-utilized and not able to meet the demand. One tactic for dealing with this situation is to make each resource more flexible so that it can serve more than one demand class. But how much flexibility should each resource have and what is the best way to deploy flexibility across the resources? This chapter shows that when done right, limited flexibility can provide almost the same level of benefits as complete flexibility.
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Notes
- 1.
1In network terminology, a chain is a connected sub-graph of the network.
- 2.
2The probabilities in the table are just the product of the probabilities for the specified demand outcomes, which are assumed to be independent; for instance, the probability for the demand case in the fifth row is found as: \(\Pr \left[ {d_b = 8,d_C = 10,d_D = 12} \right] = \Pr \left[ {d_B = 8} \right] \times \Pr \left[ {d_D = 12} \right] = \left( {{1 \over 3}} \right)^3 = {1 \over {27}} = 0.0370\)
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Acknowledgments
This research has been supported in part by the MIT Leaders for Manufacturing Program, a partnership between MIT and major manufacturing firms; and by the Singapore-MIT Alliance, an engineering education and research collaboration among the National University of Singapore, Nanyang Technological University, and MIT.
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Graves, S.C. (2008). Flexibility Principles. In: Chhajed, D., Lowe, T.J. (eds) Building Intuition. International Series in Operations Research & Management Science, vol 115. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73699-0_3
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