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Improving the Competitive Ratios of the Seat Reservation Problem

机译:提高座位预订问题的竞争率

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In the seat reservation problem, there are k stations, s_1 through s_k, and one train with n seats departing from the station s_1 and arriving at the station s_k- Each passenger orders a ticket from station s_i to station s_j (1 ≤ i ≤ j ≤ k) by specifying i and j. The task of an online algorithm is to assign one of n seats to each passenger online, i.e., without knowing future requests. The purpose of the problem is to maximize the total price of the sold tickets. There are two models, the unit price problem and the proportional price problem, depending on the pricing policy of tickets. In this paper, we improve upper and lower bounds on the competitive ratios for both models: For the unit price problem, we give an upper bound of 4/k-2k-1+4~(1//2) which improves thernprevious bound of 8/k+5. We also give an upper bound of 2/k-2 k-1+2~(1/2)rnthe competitive ratio of Worst-Fit algorithm, which improves the previous bound of 4/k-1. For the proportional price problem, we give upper andrnlower bounds of 3+13~(1/2)/k-1+13~(1/2) (approx=6.6/k+2.6) and 2/k-1,respectively, on the competitive ratio, which improves the previous bounds of 4+2 13~(1/2)/k+3+2 13~(1/2)(approx=11.2/k+10.2) and 1/k-1, respectively.
机译:在座位预订问题中,有k个车站,从s_1到s_k,以及一列火车,其中n个座位从车站s_1出发并到达车站s_k。每个乘客都从车站s_i订购到车站s_j的车票(1≤i≤j ≤k)通过指定i和j。在线算法的任务是为每个乘客在线分配n个座位之一,即不知道将来的请求。问题的目的是使所售票的总价格最大化。根据门票的定价策略,有两种模型,即单价问题和比例价格问题。在本文中,我们改进了两种模型的竞争比率的上限和下限:对于单价问题,我们给出了4 / k-2k-1 + 4〜(1 // 2)的上限,从而提高了先前的界限8 / k + 5。我们还给出了Worst-Fit算法竞争比的2 / k-2 k-1 + 2〜(1/2)的上限,从而提高了先前的4 / k-1界限。对于比例价格问题,我们分别给出上下限3 + 13〜(1/2)/ k-1 + 13〜(1/2)(大约= 6.6 / k + 2.6)和2 / k-1 ,提高了竞争比,从而提高了以前的极限4 + 2 13〜(1/2)/ k + 3 + 2 13〜(1/2)(大约= 11.2 / k + 10.2)和1 / k-1 , 分别。

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