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Enhanced Moth Search Algorithm for the Set-Union Knapsack Problems

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冯艳红 封面图
冯艳红 (Yanhong Feng)
J
Jiao-Hong Yi *
G
Gai‐Ge Wang
DOI:10.1109/ACCESS.2019.2956839delete
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摘要

摘要

En 中文
As an important and novel model with multitudinous practical applications, the set-union knapsack problem (SUKP) is a challenging issue in combinatorial optimization. In this paper, we present an enhanced moth search algorithm (EMS) for solving SUKP, which introduces an enhanced interaction operator (EIO) by integrating differential mutation into the global harmony search and then Levy flight is replaced by EIO. Comparative experimental results, which were conducted on three types of 30 popular SUKP benchmark instances, demonstrate that EMS algorithm is superior to or competitive with the other state-of-the-art metaheuristic algorithm. In particular, EMS reaches the best-known solutions for the great majority of test instances and improves the best-known solutions for six instances. Two critical ingredients of EIO is investigated to confirm their impact on the performance of EMS. The results show that both components have an important role in improving the performance of EMS.
Keyword:
Differential mutation
global harmony search
moth search algorithm
set-union knapsack problem
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IEEE Access
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Global-best harmony search
err2008-05-01
err680
PREAI
errOmran, Mahamed G. H.; Mahdavi, Mehrdad
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