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首页> 外文期刊>International journal of swarm intelligence research >Performance Comparison of Cuckoo Search Algorithm to Solve the Hybrid Flow Shop Scheduling Benchmark Problems with Makespan Criterion
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Performance Comparison of Cuckoo Search Algorithm to Solve the Hybrid Flow Shop Scheduling Benchmark Problems with Makespan Criterion

机译:布谷鸟搜索算法解决基于Makespan准则的混合Flow Shop调度基准问题的性能比较

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摘要

In this work, the performance of cuckoo search algorithm (CSA) is measured solving the multistage hybrid flow shop (HFS) scheduling problems with parallel machines. The objective is the minimization of makespan. The HFS scheduling problems are proved to be strongly non-deterministic polynomial time-hard (NP-hard). Proposed CSA algorithm has been tested on benchmark problems addressed in the literature against other well-known algorithms. The results are presented in terms of percentage deviation (PD) of the solution from the lower bound. The results indicate that the proposed CSA algorithm is quite effective in reducing makespan because average PD is observed as 1.531, whereas the next best algorithm has result of average PD of 2.295 which is in general nearly 50% worse and other algorithms start from 3.833.
机译:在这项工作中,测量了布谷鸟搜索算法(CSA)的性能,以解决并行计算机的多级混合流水车间(HFS)调度问题。目的是使制造期最小化。事实证明,HFS调度问题是强不确定性的多项式时间困难(NP-hard)。提出的CSA算法已经针对其他知名算法针对文献中提到的基准问题进行了测试。结果以溶液与下限的百分比偏差(PD)表示。结果表明,由于观察到的平均PD为1.531,因此提出的CSA算法在降低制造期方面非常有效,而次佳算法的平均PD为2.295,通常比后者差近50%,其他算法的起始值为3.833。

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