本文選題：協(xié)同學(xué)習(xí)　切入點：置換流水車間調(diào)度　出處：《控制與決策》2017年01期 　論文類型：期刊論文

【摘要】：在人工蜜蜂群算法的基礎(chǔ)上,提出一種雙種群協(xié)同學(xué)習(xí)算法.該算法根據(jù)個體適應(yīng)度高低把蜜蜂群劃分為兩個子群,并重新定義子群的學(xué)習(xí)交流機(jī)制.在10個常用的基準(zhǔn)測試函數(shù)上與其他4個常用的群體智能算法進(jìn)行比較,比較結(jié)果表明,所提出算法的性能有明顯改進(jìn).采用雙種群協(xié)同學(xué)習(xí)算法求解置換流水車間調(diào)度問題,在一些著名的中大規(guī)模測試問題包括21個Reeves實例和40個Taillard實例上進(jìn)行測試,結(jié)果表明,所提出的算法優(yōu)于其他算法,能有效解決置換流水車間調(diào)度問題.
[Abstract]:Based on the artificial bee colony algorithm, a two-population cooperative learning algorithm is proposed, which divides the bee colony into two subgroups according to the individual fitness. The learning communication mechanism of the subgroup is redefined and compared with the other four swarm intelligence algorithms on 10 common benchmark functions. The results show that, The performance of the proposed algorithm is improved obviously. A two-population cooperative learning algorithm is used to solve the permutation income job-shop scheduling problem. The results show that the proposed algorithm is tested on 21 Reeves instances and 40 Taillard instances in some famous medium-large-scale test problems. The proposed algorithm is superior to other algorithms and can effectively solve the displacement income job shop scheduling problem.
【作者單位】： 中國科學(xué)院沈陽自動化研究所;中國科學(xué)院大學(xué);
【基金】：國家杰出青年科學(xué)基金項目(61174164,51205389) 遼寧省自然科學(xué)基金項目(2015020163)
【分類號】：TP181;TB497
，

本文編號：1644364