Bin-completion, a bin-oriented branch-and-bound approach, was recently shown to be promising for the bin packing problem. We propose several improvements to bin-completion that significantly improves search efficiency. We also show the generality of bin-completion for packing and covering problems involving multiple containers, and present bin-completion algorithms for the multiple knapsack, bi...

The study documented three-dimensional spinal loading during lifting from an industrial bin. Two lifting styles and two bin design factors were examined in Phase I. The lifting style measures in Phase I were one hand versus two hand and standing on one foot versus two feet. The bin design variables were region of load in the bin and bin height. The Phase II study examined one-handed lifting sty...

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 si ∈ [0, 1] and a color ci ∈ 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 ...

We consider three variants of the open-end bin packing problem. Such variants of bin packing allow the total size of items packed into a bin to exceed the capacity of a bin, provided that a removal of the last item assigned to a bin would bring the contents of the bin below the capacity. In the first variant, this last item is the minimum sized item in the bin, that is, each bin must satisfy th...

Many combinatorial optimization problems such as the bin packing and multiple knapsack problems involve assigning a set of discrete objects to multiple containers. These problems can be used to model task and resource allocation problems in multi-agent systems and distributed systems, and can also be found as subproblems of scheduling problems. We propose bin completion, a branch-and-bound stra...

An instance of the classical bin packing problem consists of a positive real C and a list L = (a1, a2, ..., an) of items with sizes 0 < s(ai) ≤ C, 1 ≤ i ≤ n; a solution to the problem is a partition of L into a minimum number of blocks, called bins, such that the sum of the sizes of the items in each bin is at most the capacity C. The capacity is just a scaling parameter; as is customary, we pu...