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parallel bat algorithm for optimizing makespan in job shop scheduling problems

JOURNAL OF INTELLIGENT MANUFACTURING 2018年第2期29卷 451-462页

作者： Thi-Kien Dao Pan, Tien-Szu Trong-The Nguyen Pan, Jeng-Shyang Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung Taiwan Fujian Univ Technol Coll Informat Sci & Engn Fuzhou Fujian Peoples R China

parallel processing plays an important role in efficient and effective computations of function optimization. In this paper, an optimization algorithm based on parallel versions of the bat algorithm (BA), random-key encoding scheme, communication strategy scheme and makespan scheme is proposed to solve the NP-hard job shop scheduling problem. The aim of the parallel BA with communication strategies is to correlate individuals in swarms and to share the computation load over few processors. Based on the original structure of the BA, the bat populations are split into several independent groups. In addition, the communication strategy provides the diversity-enhanced bats to speed up solutions. In the experiment, forty three instances of the benchmark in job shop scheduling data set with various sizes are used to test the behavior of the convergence, and accuracy of the proposed method. The results compared with the other methods in the literature show that the proposed scheme increases more the convergence and the accuracy than BA and particle swarm optimization.

关键词： parallel bat algorithm Job shop scheduling problem Swarm intelligence

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parallel bat algorithm Applied to the Economic Load Dispatch Problem

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JOURNAL OF INTERNET TECHNOLOGY 2016年第4期17卷 761-769页

作者： Tsai, Cheng-Fu Thi-Kien Dao Pan, Tien-Szu Trong-The Nguyen Chang, Jui-Fang Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung 80778 Taiwan

In this paper, a novel optimization algorithm based on parallel version of bat algorithm (PBA) with communication strategy is proposed to solve the numerical optimization problems and the economic load dispatch problem (ELD). The aim of the parallel bat algorithm with communication strategies is to correlate individuals in swarm and to share the computation load over few processors. Based on the original structure of the bat algorithm (BA), the bat populations are split into several independent groups. In addition, the communication strategy provides the information flow for the bats to communicate in different groups. In the experiment, a set of benchmark functions and the ELD are used to test the behavior of convergence, the accuracy, and the speed of the PBA method. According to the experimental results, this novel method with communicational strategy increases the accuracy of the BA on finding the better solution. Compared with the genetic algorithm (GA) method and the particle swarm optimization (PSO) method. The experimental results are shown that the proposed PBA method can provide the higher efficiency and accuracy.

关键词： parallel bat algorithm Economic load dispatch bat algorithm

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