郑州大学学报（工学版）2024，Vol.45Issue(3)：111-118,8.DOI:10.13705/j.issn.1671-6833.2024.03.012
改进天牛群算法在柔性作业车间调度中的应用
Improved Beetle Swarm Optimization Algorithm for Flexible Job-shop Scheduling
摘要
Abstract
To solve the flexible job shop scheduling problem(FJSP),a hybrid Levy flight,reverse search,and pa-rameter adaptive adjustment strategy improved beetle swarm optimization(LRA-BSO)was proposed based on the beetle antennae search algorithm which could simulate the foraging behavior of beetles in nature and the swarm in-telligence optimization theory.Firstly,a FJSP model was established.Secondly,the initial population was genera-ted based on the Tent chaotic mapping,which would improve the quality of the initial population.Then,the Levy flight strategy and reverse search strategy were used to improve the global search ability of the LRA-BSO algorithm,and the search step size and the search distance of the beetle swarm were adjusted through fitness feedback to avoid falling into local optimum.Finally,the optimization ability of the algorithm was validated through 6 multi-dimen-sional standard test functions.In addition,the applicability of the LRA-BSO algorithm in FJSP was verified by 10 standard test cases and 1 practical case.The test results showed that the algorithm performed better or equal to oth-er intelligent optimization algorithms in eight standard test cases and demonstrated good optimization ability.In the practical cases,the improved algorithm had a 48%improvement in convergence speed compared to the original bee-tle swarm optimization algorithm.关键词
柔性作业车间调度/天牛群算法/莱维飞行策略/反向搜索策略/自适应参数调整Key words
flexible job-shop scheduling/beetle swarm optimization/Levy flight/reverse search/adaptive parame-ter adjustment分类
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丁凯,赵欣悦,吕景祥,朱斌..改进天牛群算法在柔性作业车间调度中的应用[J].郑州大学学报（工学版）,2024,45(3):111-118,8.基金项目
国家自然科学基金资助项目(51705030) （51705030）
中国博士后科学基金特别资助项目(2022T150073) （2022T150073）
