The following online bin packing problem is considered: Items with integer sizes are given and variable sized bins arrive online. A bin must be used if there is still an item remaining which fits in it when the bin arrives. The goal is to minimize the total size of all the bins used. Previously, a lower bound of 5 4 on the competitive ratio of this problem was achieved using jobs of size S and ...

In this paper, we study the following knapsack problem: Given a list of squares with profits, we are requested to pack a sublist of them into a rectangular bin (not a unit square bin) to make profits in the bin as large as possible. We first observe there is a Polynomial Time Approximation Scheme (PTAS) for the problem of packing weighted squares into rectangular bins with large resources, then...

The bin packing problem (BP) consists in finding the minimum number of bins necessary to pack a set of items so that the total size of the items in each bin does not exceed the bin capacity C. The bin capacity is common for all the bins. This problem can be solved in Constraint Programming (CP) by introducing one placement variable xi for each item and one load variable lj for each bin. The Pac...

Suppose we sequentially put n balls into n bins. If we put each ball into a random bin then the heaviest bin will contain ∼ logn/ log logn balls with high probability. However, Azar, Broder, Karlin and Upfal [SIAM J. Comput. 29 (1999) 180–200] showed that if each time we choose two bins at random and put the ball in the least loaded bin among the two, then the heaviest bin will contain only ∼ l...

Bin packing is a well-known NP-Hard optimization problem which has several real applications. Classical bin packing (BPP) is a simple model where all bins are identical. However, the variable sized bin packing problem (VSBPP) is a generalization of the bin packing problem where bins of different capacities are available for packing a set of items having different weights. The objective is to pa...

We consider a generalized one-dimensional bin packing model in which the cost of a bin is a nondecreasing concave function of the utilization of the bin. We show that for any given positive constant , there exists a polynomial-time approximation algorithmwith an asymptotic worst-case performance ratio of no more than 1 + .

A study was undertaken to investigate the effect of liquid nitrogen aeration on mortalities of adult Cryptolestes furrugineus, rusty grain beetles, in a prototype cardboard grain bin equipped with an aeration system. The grain bin was filled with Hard Red Spring wheat and liquid nitrogen was introduced from the bottom of the bin. The survival of both cold acclimated and unacclimated C. furrugin...

MsatAllele is a computer package built on R to visualize and bin the raw microsatellite allele size distributions. The method is based on the creation of an R database with exported files from the open-source electropherogram peak-reading program STRAND. Contrary to other binning programs, in this program, the bin limits are not fixed and are automatically defined by the data stored in the data...

By jointly analyzing multiple variants within a gene together, instead of one at a time, gene-based regression analysis can improve power and robustness of genetic association analysis. Extending prior work that examined multi-bin linear combination (MLC) statistics for combined analysis of rare and common variants, here we investigate analysis of common variants more extensively under realisti...

Usually, for bin packing problems, we try to minimize the number of bins used or in the case of the dual bin packing problem, maximize the number of accepted items or accepted volume. This paper presents results for the opposite problems, where we want to maximize the number of bins used or minimize the number of accepted items or the accepted volume. For the off-line variant, we require that t...