Bin packing and related problems: General arc-flow formulation with graph compression
نویسندگان
چکیده
منابع مشابه
General Arc-flow Formulation with Graph Compression
We present an exact method, based on an arc-flow formulation with side constraints, for solving bin packing and cutting stock problems — including multi-constraint variants — by simply representing all the patterns in a very compact graph. Our method includes a graph compression algorithm that usually reduces the size of the underlying graph substantially without weakening the model. Our formul...
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The vector bin packing problem (VBP) is a generalization of bin packing with multiple constraints. In this problem we are required to pack items, represented by p-dimensional vectors, into as few bins as possible. The multiple-choice vector bin packing (MVBP) is a variant of the VBP in which bins have several types and items have several incarnations. We present an exact method, based on an arc...
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The cutting stock problem with binary patterns (0-1 CSP) is a variant of CSP that usually appears as a relaxation of 2D and 3D packing problems. We present an exact method, based on an arc-flow formulation with side constraints, for solving 0-1 CSP by simply representing all the patterns in a very compact graph. Gilmore-Gomory’s column generation approach is usually used to compute strong lower...
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VPSolver is a vector packing solver based on an arc-flow formulation with graph compression. In this paper, we present the algorithm introduced in VPSolver 3.0.0 for building compressed arc-flow models for the multiple-choice vector packing problem.
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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.
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ورودعنوان ژورنال:
- Computers & OR
دوره 69 شماره
صفحات -
تاریخ انتشار 2016