Decomposition methods are techniques for exploiting the tractable substructures of an integer program in order to obtain improved solution procedures. In particular, the goal is to derive improved methods of bounding the optimal solution value, which can then be used to drive a branch-andbound algorithm. Such methods are the preferred solution approaches for a wide range of important models ari...

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 state-of-the-art global constraint for bin packing is due to Shaw. We compare two linear continuous relaxations of the bin packing problem, based on the DP-flow and Arc-flow models, with the filtering of the bin packing constraint. Our experiments show that we often obtain significant improvements in runtime. The DP-flow model is a novel formulation of the problem.

In this paper an approximation algorithm for the three-dimensional bin packing problem is proposed and its performance bound is investigated. To obtain such a bound a modified bin packing algorithm is considered for a two-dimensional problem with bounded bin and its area utilization is estimated. Finally, a hard example gives a lower bound of the performance bound. '

Covering Tour Problem (CTP) is the generalized form of Traveling Salesman Problem (TSP), which has found different applications in the designing of distribution networks, disaster relief, and transportation routing. The purpose of this problem is to determine the Hamiltoniancyclewiththe lowest costusinga subset of all the nodes, such that the other nodes would be in a distance shorter than the ...

The bin packing optimization problem packs a set of objects into a set of bins so that the amount of wasted space is minimized The bin packing problem has many important applications These include multiprocessor scheduling resource allocation and real world planning packing routing and scheduling optimization problems The bin packing problem is NP complete Since there is therefore little hope i...

The bin packing problem has been extensively studied and numerous variants have been considered. The k-item bin packing problem is one of the variants introduced by Krause et al. in Journal of the ACM 22(4). In addition to the formulation of the classical bin packing problem, this problem imposes a cardinality constraint that the number of items packed into each bin must be at most k. For the o...

In the age of Big Data the problem of storing huge volume of data in a minimum storage space by utilizing available resources properly is an open problem and an important research aspect in recent days. This problem has a close relationship with the famous classical NP-Hard combinatorial optimization problem namely the “Bin Packing Problem” where bins represent available storage space and the p...