We formally define multi-resource bin packing, a generalization of conventional bin packing, and develop an algorithm called Reordering Grouping Genetic Algorithm (RGGA) to solve this problem. Multi-resource bin packing can be applied to different problems, such as placing virtual machines onto servers. We first test RGGA on conventional bin packing problems and show that it yields excellent re...

Online Bin Stretching is a semi-online variant of bin packing in which the algorithm has to use the same number of bins as the 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 also s...

Due to the rising trend of urbanization along with overconsumption of non-recyclable resources, the volume of municipal solid waste is increasing every day. An efficient, cost effective and environment friendly solution for real time bin statusmonitoring, collection and transportation of municipal solid waste is still a major challenge to the local municipal authorities. This research proposes ...

We consider a variant of bin packing calledmultiple-choice vector bin packing. In this problem we are given a set of n items, where each item can be selected in one of several D-dimensional incarnations. We are also given T bin types, each with its own cost and D-dimensional size. Our goal is to pack the items in a set of bins of minimum overall cost. The problem is motivated by scheduling in n...

The bin-packing problem is a well known NP-Hard optimisation problem, and, over the years, many heuristics have been developed to generate good quality solutions. This paper outlines a genetic programming system which evolves a heuristic that decides whether to put a piece in a bin when presented with the sum of the pieces already in the bin and the size of the piece that is about to be packed....

We consider two well-known natural variants of bin packing, and show that these packing problemsadmit asymptotic fully polynomial time approximation schemes (AFPTAS). In bin packing problems,a set of one-dimensional items of size at most 1 is to be assigned (packed) to subsets of sum at most1 (bins). It has been known for a while that the most basic problem admits an AFPTAS. In this...

The standard procedure for measuring correlations between pairs of spike trains is to count the numbers of spikes occurring within a specified set of time intervals partitioning the continuous time line into discrete bins of width w (seconds). One then computes the Pearson correlation between pairs of the bin occupancy vectors. This method introduces a form of quantization noise, similar to tha...

The Three Dimensional Bin Packing Problem (3DBPP) is within one of the broad categories of the Bin Packing Problem. The other broad categories include the One Dimensional and the Two Dimensional Bin Packing Problem. As we live in a three dimensional world, the 3DBPP can model a variety of real world problems. Some of the popular applications of the 3DBPP include the Container Loading Problem an...

This paper presents a new parallel indexing data structure for answering queries. The index, called Bin-Hash, offers extremely high levels of concurrency, and is therefore wellsuited for the emerging commodity of parallel processors, such as multi-cores, cell processors, and general purpose graphics processing units (GPU). The Bin-Hash approach first bins the base data, and then partitions and ...

In this paper, we consider the Generalized Bin Covering problem: We are given m bin types, where each bin of type i has profit pi and demand di. Furthermore, there are n items, where item j has size sj . A bin of type i is covered if the set of items assigned to it has total size at least the demand di. In that case, the profit of pi is earned and the objective is to maximize the total profit. ...