A Two-Pass Algorithm for Unordered Colored Bin Packing

Extending Two-Dimensional Bin Packing Problem: Consideration of Priority for Items

In this paper a two-dimensional non-oriented guillotine bin packing problem is studied when items have different priorities. Our objective is to maximize the total profit which is total revenues minus costs of used bins and wasted area. A genetic algorithm is developed to solve this problem where a new coding scheme is introduced. To evaluate the performance of the proposed GA, first an upper b...

On Solving the Oriented Two-Dimensional Bin Packing Problem under Free Guillotine Cutting: Exploiting the Power of Probabilistic Solution Construction

Two-dimensional bin packing problems are highly relevant combinatorial optimization problems. They find a large number of applications, for example, in the context of transportation or warehousing, and for the cutting of different materials such as glass, wood or metal. In this work we deal with the oriented two-dimensional bin packing problem under free guillotine cutting. In this specific pro...

Online Colored Bin Packing

In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of c ≥ 2 colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize ...

 Abstract: Packing rectangular shapes into a rectangular space is one of the most important discussions on Cutting & Packing problems (C;P) such as: cutting problem, bin-packing problem and distributor's pallet loading problem, etc. Assume a set of rectangular pieces with specific lengths, widths and utility values. Also assume a rectangular packing space with specific width and length. The obj...

On the Approximability of Geometric and Geographic Generalization and the Min-Max Bin Covering Problem

We study the problem of abstracting a table of data about individuals so that no selection query can identify fewer than k individuals. As is common in existing work on this k-anonymization problem, the means we investigate to perform this anonymization is to generalize values of quasi-identifying attributes into equivalence classes. Since such data tables are intended for use in data mining, w...