关键词: 锻造, 组批, 多目标优化, 协同决策, 多智能体, 重构, 博弈论

Abstract: To solve multi-level and multi-objective batch delivery collaboration optimization, the modeling tool was analyzed, and the modeling technology by combining Aglet based mobile Agent with Flexsim based simulation was selected. To avoid traditional multi-Agent system's shortcomings, a hybrid control structure was adopted in system. The solving frame of forging multi-level and multi-objective was designed, and multi-Agent collaboration model as well as Unified Modeling Language(UML)based collaborative process were given. An improved Look-ahead Batching Rule(LBCR)strategy based on improved Q-learning algorithm was proposed to serve as multi-level and multi -objective collaborative algorithm. The control experiment was used for production system's parameters which may affect the experiment result, and the tardiness as well as cost of different algorithms in uncertain condition were studied. The results showed that the proposed algorithm was better than the traditional LBCR strategies and the output of production system had strong stability.

Key words: forging, batch, multi-objective optimization, collaborative decision, multi-Agent, reconstruction, game theory