Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
496979 | Applied Soft Computing | 2011 | 9 Pages |
Abstract
This paper proposes a novel global harmony search algorithm (NGHS) to solve 0–1 knapsack problems. The proposed algorithm includes two important operations: position updating and genetic mutation with a small probability. The former enables the worst harmony of harmony memory to move to the global best harmony rapidly in each iteration, and the latter can effectively prevent the NGHS from trapping into the local optimum. Computational experiments with a set of large-scale instances show that the NGHS can be an efficient alternative for solving 0–1 knapsack problems.
Keywords
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Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Dexuan Zou, Liqun Gao, Steven Li, Jianhua Wu,