Results 1 
2 of
2
Nearly Optimal Competitive Online Replacement
"... This paper studies the following online replacement problem. There is a real function f(t), called the flow rate, defined over a finite time horizon [0; T ]. It is known that m f(t) M for some reals 0 m ! M . At time 0 an online player starts to pay money at the rate f(0). At each time 0 ! t T ..."
Abstract

Cited by 5 (2 self)
 Add to MetaCart
This paper studies the following online replacement problem. There is a real function f(t), called the flow rate, defined over a finite time horizon [0; T ]. It is known that m f(t) M for some reals 0 m ! M . At time 0 an online player starts to pay money at the rate f(0). At each time 0 ! t T the player may changeover and continue paying money at the rate f(t). The complication is that each such changeover incurs some fixed penalty. The player is called online as at each time t the player knows f only over the time interval [0; t]. The goal of the player is to minimize the total cost comprised of cumulative payment flow plus changeover costs. This formulation of the replacement problem has various interesting applications among which are: equipment replacement, supplier replacement, the menu cost problem and mortgage refinancing.
BlindlyCompetitive Algorithms: Pricing & Bidding as a Case Study (Extended Abstract)
, 1995
"... The standard setting for competitive analysis of online algorithms assumes that online algorithm knows the past (but not future) inputs, and can optimize its performance by "learning" from mistakes of the past. This framework cannot capture some of the reallife online decisionmaking, whi ..."
Abstract
 Add to MetaCart
The standard setting for competitive analysis of online algorithms assumes that online algorithm knows the past (but not future) inputs, and can optimize its performance by "learning" from mistakes of the past. This framework cannot capture some of the reallife online decisionmaking, which takes place without full knowledge of past and present inputs. Instead, online algorithm only knows a function (or part) of its past decisions and real inputs (which we call the hidden input). A typical example is that of economic "warfare" involving, say, two companies, and a pool of (unknown) customers. In this work, we focus on problem of pricing an interdependent collection of resources, in the absence of knowledge about the following crucial information about the past and future inputs: ffl the customers financial benefit or prices offered by the competition, ffl the duration of the contracts, and ffl the future demand for the pro...