Balls-into-bins games describe in an abstract setting several multiple-choice scenarios, and allow for a systematic and unified theoretical treatment. In the process that we consider, there are n bins, initially empty, and m = bcnc balls. Each ball chooses independently and uniformly at random k ≥ 3 bins. We are looking for an allocation such that each ball is placed into one of its chosen bins...

this study by the first, was carried out to evaluate and comparing disposal waste management in karaj's hospitals in 1387. interview and observation methods were used to collect data and the study tool was a questionnaire. data were analyzed by the spss, using chi-square and t-test. regarding the condition of infectious waste generation, 64% of the hospitals had a good grade. source separa...

ONLINE BIN STRETCHING is a semi-online variant of bin packing in which the algorithm has to use the same number of bins as an optimal packing, but is allowed to slightly overpack the bins. The goal is to minimize the amount of overpacking, i.e., the maximum size packed into any bin. We give an algorithm for ONLINE BIN STRETCHING with a stretching factor of 1.5 for any number of bins. We build o...

In the variable-sized online bin packing problem, one has to assign items to bins one by one. The bins are drawn from some xed set of sizes, and the goal is to minimize the sum of the sizes of the bins used. We present the rst unbounded space algorithms for this problem. We also show the rst lower bounds on the asymptotic performance ratio. The case where bins of two sizes, 1 and 2 (0; 1), are ...

Multiple-choice allocation algorithms have been studied intensively over the last decade. These algorithms have several applications in the areas of load balancing, routing, resource allocation and hashing. The underlying idea is simple and can be explained best in the balls-and-bins model: Instead of assigning balls (jobs, requests, or keys) simply at random to bins (machines, servers, or posi...

This paper presents the CBIR based on bins approach. It introduces a new idea of partitioning the histogram into three parts using Centre of gravity. This partitioning leads to generation of 27 bins. In this work we have tried to reduce the feature vector dimension to just 27 bins out of 256 histogram bins. This paper elaborates the bins approach using linear (LP) and centre of gravity (CG) bas...

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...

We consider the bin-packing problem with the constraint that the elements are in the plane, and only elements within an oriented unit square can be placed within a single bin. The elements are of given weights, and the bins have unit capacities. The problem is to minimize the number of bins used. Since the problem is obviously NP-hard, no algorithm is likely to solve the problem optimally in be...