本文關(guān)鍵詞： 作業(yè)車間調(diào)度(JSP) 多智能體 遺傳算法 鄰居交互算子 自適應模擬退火算法(ASA)　出處：《北京航空航天大學學報》2017年02期 　論文類型：期刊論文

【摘要】：針對作業(yè)車間調(diào)度問題(JSP)的非確定性多項式特性與解空間分布的大山谷屬性,本文提出一種多智能體遺傳算法(MAGA)與自適應模擬退火算法(ASA)的混合優(yōu)化算法,用于尋找最大完工時間最短的調(diào)度。首先,將每個染色體視作獨立的智能體并采用工序編碼方式隨機初始化每個智能體,結(jié)合多智能體協(xié)作與競爭理論設(shè)計了實現(xiàn)智能體之間交互作用的鄰居交互算子,進而利用一定數(shù)量智能體進行全局搜索,找到多個適應度較高的可行解。其次,為避免算法陷入局部最優(yōu),采用ASA對每個智能體開展局部尋優(yōu)。最后,通過基準測試庫中典型實例的計算結(jié)果驗證了該算法的有效性。
[Abstract]:For the Job-shop scheduling problem (JSP), the non-deterministic polynomial property and the large valley attribute of the solution space distribution are discussed. In this paper, a hybrid optimization algorithm named Multi-Agent genetic algorithm (MAGA) and Adaptive simulated annealing algorithm (ASA) is proposed, which is used to find the schedule with the shortest completion time. Each chromosome is regarded as an independent agent and each agent is initialized randomly by the process coding method. A neighbor interaction operator is designed to realize the interaction between agents combined with the theory of multi-agent cooperation and competition. Then a certain number of agents are used for global search to find several feasible solutions with high fitness. Secondly, in order to avoid the algorithm falling into local optimum, ASA is used to carry out local optimization for each agent. Finally. The validity of the algorithm is verified by the calculation results of typical examples in the benchmark library.
【作者單位】： 北京航空航天大學機械工程及自動化學院;
【基金】：國家重大科技專項(2015ZX04005005)~~
【分類號】：TP18;TB497
【正文快照】： 網(wǎng)絡(luò)出版地址:www.cnki.net/kcms/detail/11.2625.V.20160307.1508.001.html引用格式:李小濤,彭，

本文編號：1451477