【摘要】：針對遺傳算法在求解裝配序列規(guī)劃問題中速度慢、產(chǎn)生重復(fù)解等問題,提出一種將螞蟻算法、混沌算法和遺傳算法結(jié)合,加入動態(tài)更新種群數(shù)目這一策略的新方法。利用拆卸干涉矩陣獲取零件之間的信息,建立評優(yōu)指標的信息矩陣。算法前期采用螞蟻算法進行局部搜索,后期運用混沌—遺傳算法進行全局搜索。在全局搜索中,采用Logistic映射生成子代裝配序列以避免產(chǎn)生重復(fù)解,并設(shè)置一定的比例篩選搜索結(jié)果,動態(tài)更新種群數(shù)目。為進一步提高序列優(yōu)劣的區(qū)分度,將裝配工具的運用次數(shù)與裝配方向的改變次數(shù)合并為連貫性,同時引入輔助工具這一指標。以齒輪油泵為例,將所提算法與螞蟻算法、遺傳算法和混合算法進行比較,從適應(yīng)度值、運行時間和收斂速度方面進行分析,驗證了該算法的有效性。
[Abstract]:Aiming at the problem of slow speed and repeated solution in solving assembly sequence planning problem by genetic algorithm, a new method which combines ant algorithm, chaos algorithm and genetic algorithm to dynamically update population number is proposed. The disassembly interference matrix is used to obtain the information between parts, and the information matrix of the evaluation index is established. Ant algorithm is used for local search and chaos-genetic algorithm is used for global search. In the global search, the assembly sequence of offspring is generated by Logistic mapping to avoid repeated solutions, and a certain proportion is set to filter the search results and dynamically update the population number. In order to improve the classification of the sequence, the combination of the number of the assembly tools and the changing times of the assembly direction into the coherence, and the introduction of the auxiliary tool as the index at the same time. Taking the gear pump as an example, the proposed algorithm is compared with ant algorithm, genetic algorithm and hybrid algorithm. The validity of the proposed algorithm is verified in terms of fitness, running time and convergence speed.
【作者單位】： 桂林電子科技大學(xué)廣西可信軟件重點實驗室;
【基金】：國家自然科學(xué)基金資助項目(61100025,61262030,61363030) 廣西自然科學(xué)基金資助項目(2014GXNSFAA118354)~~
【分類號】：TG95;TP18

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1 丁慧敏,李蓓智,周亞琴;基于遺傳算法的裝配序列規(guī)劃[J];東華大學(xué)學(xué)報(自然科學(xué)版);2001年06期

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