The Bin Packing Problem is one of the most important optimization problems. In recent years, due to its NP-hard nature, several approximation algorithms have been presented. It is proved that the best algorithm for the Bin Packing Problem has the approximation ratio 3/2 and the time orderO(n), unlessP=NP. In this paper, first, a -approximation algorithm is presented, then a modification to FFD ...

In this paper, we consider the two-dimensional variable-sized bin packing problem (2DVSBPP) with guillotine constraint. 2DVSBPP is a well-known NP-hard optimization problem which has several real applications. A mixed bin packing algorithm (MixPacking) which combines a heuristic packing algorithm with the Best Fit algorithm is proposed to solve the single bin problem, and then a backtracking al...

This paper proposes a visualization tool for analyzing the behavior of metaheuristic algorithms. It works by reproducing graphically the solutions generated in execution time. The tool was evaluated analyzing the Hybrid Grouping Genetic Algorithm for Bin Packing (HGGA_BP). It was used to solve a benchmark with 17 instances of the one dimensional Bin Packing problem (1D-BPP). The use of the visu...

The two-dimensional discrete bin-packing problem (2BP ) consists in minimizing the number of identical rectangles used to pack a set of smaller rectangles. This problem is NP-complete. It occurs in industry if pieces of steel, wood, or paper have to be cut from larger rectangles. It belongs to the family of cutting and packing (C & P) problems, more precisely Two-Dimensional Single Bin Size Bin...

line and oo-line approximation algorithms for vector covering problems. analysis of algorithms for dual bin packing problems. packing can be solved within 1 + in linear time.gorithms for the m-dimensional 0-1 knapsack problem: worst-case and probabilistic analyses.schatz. Resource scheduling in enhanced pay-per-view continuous media databases. An eecient approximation scheme for the one-dimensi...

In this paper, we consider the three-dimensional orthogonal bin packing problem, which is a generalization of the well-known bin packing problem. We present new lower bounds for the problem and demonstrate that they improve the best previous results. The asymptotic worst-case performance ratio of the lower bounds is also proved. In addition, we study the non-oriented model, which allows items t...

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 this paper, we present an O(n1ogn) algorithm to compute a tighter lower bound for the one-dimensional bin packing problem. We have simulated the algorithm on randomly generated bin packing problems with item sizes drawn uniformly from (a, b], where 0 5 a < b 5 B and B is bin size. Using our lower bound, the average error of BFD is less than 2%. For a + b > B, the error is less than 0.003%. K...