We study the following problem, introduced by in 2006. We are given, online or offline, a set of coloured items of different sizes, and wish to pack them into bins of equal size so that we use few bins in total (at most α times optimal), and that the items of each colour span few bins (at most β times optimal). We call such allocations ( α , β ) -approximate. As usual in bin packing problems, we allow additive constants and consider ( α , β ) as the asymptotic performance ratios. We prove that for e 0 , if we desire small α, no scheme can beat ( 1 + e , ? ( 1 e ) ) -approximate allocations and similarly as we desire small β, no scheme can beat ( 1.69103 , 1 + e ) -approximate allocations. We give offline schemes that come very close to achieving these lower bounds. For the online case, we prove that no scheme can even achieve ( O ( 1 ) , O ( 1 ) ) -approximate allocations. However, a small restriction on item sizes permits a simple online scheme that computes ( 2 + e , 1.7 ) -approximate allocations.
There are some other variants of bin packing problems with colours, for example the so called Colored Bin Packing that has the restriction that items of a same colour cannot be packed next to each other on a same bin. Approximation algorithms for the online version of the problem were presented by B "o @cite_14 and Dosa and Epstein @cite_9 . A generalization where the objective is to pack a graph @math into another graph @math where nodes into @math have capacities and nodes in @math corresponds to items of given size, was studied by Bujt 'a in @cite_0
@cite_0 @cite_9 @cite_14
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We study a variant of online bin packing, called colorful bin packing. In this problem, items that are presented one by one are to be packed into bins of size 1. Each item i has a size s i ∈ [0,1] and a color (c_i C ), where ( C ) is a set of colors (that is not necessarily known in advance). The total size of items packed into a bin cannot exceed its size, thus an item i can always be packed into a new bin, but an item cannot be packed into a non-empty bin if the previous item packed into that bin has the same color, or if the occupied space in it is larger than 1 − s i . This problem generalizes standard online bin packing and online black and white bin packing (where (| C |=2 )). We prove that colorful bin packing is harder than black and white bin packing in the sense that an online algorithm for zero size items that packs the input into the smallest possible number of bins cannot exist for (| C | 3 ), while it is known that such an algorithm exists for (| C |=2 ). We show that natural generalizations of classic algorithms for bin packing fail to work for the case (| C | 3 ), and moreover, algorithms that perform well for black and white bin packing do not perform well either, already for the case (| C |=3 ). Our main results are a new algorithm for colorful bin packing that we design and analyze, whose absolute competitive ratio is 4, and a new lower bound of 2 on the asymptotic competitive ratio of any algorithm, that is valid even for black and white 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. We consider a particular bin packing problem in which some pairs of items may be in conflict and cannot be assigned to the same bin. The problem, denoted as the bin packing problem with conflicts, is of practical and theoretical interest because of its many real-world applications and because it generalizes both the bin packing problem and the vertex coloring problem. We present new lower bounds, upper bounds, and an exact approach, based on a set covering formulation solved through a branch-and-price algorithm. We investigate the behavior of the proposed procedures by means of extensive computational results on benchmark instances from the literature. In this paper we consider the following bin packing problem with conflicts. Given a set of items V = 1,...,n with sizes s 1 ,...,s n ∈ (0,1) and a conflict graph G = (V, E), we consider the problem to find a packing for the items into bins of size one such that adjacent items (j, j') ∈ E are assigned to different bins. The goal is to find an assignment with a minimum number of bins. This problem is a natural generalization of the classical bin packing problem. We propose an asymptotic approximation scheme for the bin packing problem with conflicts restricted to d-inductive graphs with constant d. This graph class contains trees, grid graphs, planar graphs and graphs with constant treewidth. The algorithm finds an assignment for the items such that the generated number of bins is within a factor of (1 + ∈) of optimal provided that the optimum number is sufficiently large. The running time of the algorithm is polynomial both in n and in 1 2.