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...

The work considers the problem of three-dimensional bin packaging (3D-BPP), where a load of maximum volume is put in a single container. To solve the above mentioned problem there was a coevolutionary parallel algorithm used basing on the separate evolution of cooperating subpopulations of possible solutions. Computational experiments were conducted in a neighbourhood of clusters and aimed to e...

We consider the two-dimensional bin packing problem (BPP): given a set of rectangular items, find the minimal number of rectangular bins needed to pack all items. Rotation of the items is not permitted. We show for any integer k ≥ 3 that at most k − 1 bins are needed to pack all items if every item fits into a bin and if the total area of items does not exceed k/4-times the bin area. Moreover, ...

The bin packing problem is to find the minimum number of bins of size one to pack a list of items with sizes a1, . . . , an in (0, 1]. Using uniform sampling, which selects a random element from the input list each time, we develop a randomized O( n)(log log n) ∑n i=1 ai +( 1 2 ) 1 2 ) time (1+2)approximation scheme for the bin packing problem. We show that every randomized algorithm with unifo...

In this paper, we present improved bounds for the First Fit algorithm for the bin-packing problem.We prove C FF (L) ≤ 17 10C (L)+ 7 10 for all lists L, and the absolute performance ratio of FF is at most 12 7 . © 2010 Elsevier B.V. All rights reserved.

We consider the NP Hard problems of online Bin Covering and Packing while requiring that larger (or longer, in the one dimensional case) items be placed at the bottom of the bins, below smaller (or shorter) items — we call such a version, the LIB version of problems. Bin sizes can be uniform or variable. We look at computational studies for both the Best Fit and Harmonic Fit algorithms for unif...

This paper presents the use of genetic algorithms (GA) for solving the dual bin packing problem using fuzzy objectives. In bin packing problems, a list, L of items is to be packed into a minimum number of bins. In dual bin packing the items are packed into a maximum number of bins, assuring a minimum weight for each bin. We consider a class which we call dynamic dual bin packingg. Similar to th...