Multi-threaded bacterial Iterated Greedy heuristics for the Permutation Flow Shop Problem
Multi-threaded bacterial Iterated Greedy heuristics for the Permutation Flow Shop Problem
复制标题
排列流水车间问题的多线程细菌迭代贪婪启发法
DOI：
10.1109/cinti.2012.6496734
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
L. Kóczy
中科院分区：
文献类型：
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作者：
K. Balázs;Z. Horváth;L. Kóczy
本文提出的方法相结合的迭代贪婪技术，作为国家的最先进的方法，细菌进化算法的基础上的混合技术，涉及多线程迭代贪婪启发式和模因算法，以有效地解决排列流水车间问题的并行计算架构。在目前的工作中，提出了三种新的方法相结合的细菌Memetic算法的变体和最近提出的细菌迭代贪婪技术与上述混合多线程的方法。由此获得的技术进行评估，通过模拟运行的一系列数据从著名的Taillard的基准问题集。基于实验结果的多线程的混合方法进行了比较，彼此和原始技术（即没有细菌算法的技术）。
This paper proposes approaches for combining Iterated Greedy techniques, as state-of-the-art methods, with bacterial evolutionary algorithms based on a hybrid technique involving the Multi-Threaded Iterated Greedy heuristic and a memetic algorithm in order to efficiently solve the Permutation Flow Shop Problem on parallel computing architectures. In the present work three novel approaches are proposed by combining a variant of the Bacterial Memetic Algorithm and the recently proposed Bacterial Iterated Greedy technique with the mentioned hybrid multi-threaded approach. The techniques thus obtained are evaluated via simulation runs carried out on a series of data from the well-known Taillard's benchmark problem set. Based on the experimental results the multi-threaded hybrid methods are compared to each other and to the original techniques (i.e. to the techniques without bacterial algorithms).