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Abstract
In the Multislope Ski Rental problem, the user needs a certain resource for some unknown period of time. To use the resource, the user must subscribe to one of several options, each of which consists of a onetime setup cost (``buying price''), and cost proportional to the duration of the usage (``rental rate''). The larger the price, the smaller the rent. The actual usage time is determined by an adversary, and the goal of an algorithm is to minimize the cost by choosing the best option at any point in time. Multislope Ski Rental is a natural generalization of the classical Ski Rental problem (where the only options are pure rent and pure buy), which is one of the fundamental problems of online computation. The Multislope Ski Rental problem is an abstraction of many problems where online decisions cannot be modeled by just two options, e.g., power management in systems which can be shut down in parts. In this paper we study randomized algorithms for Multislope Ski Rental. Our results include the best possible online randomized strategy for any additive instance, where the cost of switching from one option to another is the difference in their buying prices; and an algorithm that produces an ecompetitive randomized strategy for any (nonadditive) instance.
Original language  American English 

Media of output  Topical/Group Seminar 
Place of Publication  City University of New York; Faculty of Engineering 
State  Published  7 Oct 2015 
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 1 Oral presentation

Topical/Group Seminar: Rent, lease or buy: randomized strategies for multislope ski rental
Rawitz, D. (Speaker)
7 Oct 2015 → …Activity: Talk or presentation › Oral presentation