Randomized Minmax Regret for Combinatorial Optimization Under Uncertainty
The minmax regret problem for combinatorial optimization under uncertainty can be viewed as a zero-sum game played between an optimizing player and an adversary, where the optimizing player selects a solution and the adversary selects costs with the intention of maximizing the regret of the player....
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Springer-Verlag
2017
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| Online Access: | http://hdl.handle.net/1721.1/110966 https://orcid.org/0000-0002-8585-6566 |