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Real Life is Taylor's first novel; he is a "scientist turned novelist" who did his undergraduate studies at Auburn University Montgomery. [2] Charles Arrowsmith, writing for The Washington Post, said that "Like many first novels, Real Life appears to hew to its author's own experience—Taylor has written in numerous personal essays about being gay and Southern, his abusive upbringing and his ...
Many of these problems can be related to real-life packaging, storage and transportation issues. Each packing problem has a dual covering problem, which asks how many of the same objects are required to completely cover every region of the container, where objects are allowed to overlap. In a bin packing problem, people are given:
Many techniques from bin packing are used in this problem too. [52] In the guillotine cutting problem, both the items and the "bins" are two-dimensional rectangles rather than one-dimensional numbers, and the items have to be cut from the bin using end-to-end cuts. In the selfish bin packing problem, each item is a player who wants to minimize ...
In the bin packing problem, there are n items with different sizes. The goal is to pack the items into a minimum number of bins, where each bin can contain at most B. A feasible configuration is a set of sizes with a sum of at most B. Example: [7] suppose the item sizes are 3,3,3,3,3,4,4,4,4,4, and B=12. Then the possible configurations are ...
Taylor's book tour to publicize his novel was cut short by the COVID-19 pandemic and associated restrictions on travel and public gatherings. [26] Real Life was shortlisted for the 2020 Booker Prize. [27] The New York Times included the novel on its list of "100 Notable Books of 2020". [28]
For each item from largest to smallest, find the first bin into which the item fits, if any. If such a bin is found, put the new item in it. Otherwise, open a new empty bin put the new item in it. In short: FFD orders the items by descending size, and then calls first-fit bin packing. An equivalent description of the FFD algorithm is as follows.
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This problem is a dual of the bin packing problem: in bin covering, the bin sizes are bounded from below and the goal is to maximize their number; in bin packing, the bin sizes are bounded from above and the goal is to minimize their number. [1] The problem is NP-hard, but there are various efficient approximation algorithms: