关键词: Multi-Agent, 人工神经网络, 响应面, 协同优化

Abstract:

Based on the principles of collaborative optimization, this paper presented an intelligent Multi-Agent model, which employed ANN to build response surface of subspace agent, and used subtask-programming agent to perform the traditional optimization processing. By the approximate satisfactory degree calculated by result analysis agent, task assignment agent was able to select different executive routes autonomously. The response surface agent acquired gradually the accurate response surface of subspace objects and constrainted in accordance with updating criterion. When subspace agent received the target vector from system level, it can use the response surface to fastly produce the optimal solution and sent it to global blackboard structure, by which system level agent coordinated the inconsistent information of different subspace agents. Finally, an engineering example was applied to prove the proposed method can improve the efficiency and accuracy of collaborative optimization for complex mechanical products.

Key words: Multi-Agent, ANN, response surface, collaborative optimization