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- W2318421611 abstract "Many combinatorial optimization problems involve packing some set of discrete objects into multiple containers. In this dissertation, we study bin completion, a branch-and-bound approach to optimally solving one-dimensional, multicontainer packing problems. Bin completion combines a bin-oriented search space with a powerful dominance criterion that enables us to prune much of the space. We investigate a number of extensions to bin completion that significantly improves search efficiency, including variable and value ordering heuristics, and a nogood dominance pruning technique that allows further exploitation of the dominance criterion. Bin completion is applied to four problems: multiple knapsack, bin covering, min-cost covering, and bin packing. We show that our bin-completion algorithms yield new, state of the art results for the multiple knapsack, bin-covering, and min-cost covering problems, outperforming previous algorithms by orders of magnitude with respect to runtime. For example, previous solvers for the multiple knapsack problem were unable to solve instances with 15 containers and 30 items given a time limit of 300 seconds per problem. Our solver solves all such instances in an average time of less than 0.05 seconds. For the bin packing problem, we demonstrate significant improvements compared to most previous results, but show that bin completion is not competitive with current state-of-the-art cutting-stock based approaches." @default.
- W2318421611 created "2016-06-24" @default.
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- W2318421611 date "2005-01-01" @default.
- W2318421611 modified "2023-09-26" @default.
- W2318421611 title "Bin completion algorithms for packing and knapsack problems" @default.
- W2318421611 hasPublicationYear "2005" @default.
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