【摘要】 针对制造过程因动态多变而难以定量控制的问题,提出了用集成计算智能方法进行多目标优化。利用人工神经网络进行系统建模,并为遗传算法找到适应度函数及求得目标函数值的方法,进而利用遗传算法进行多目标优化。通过实例验证了方法的有效性与实用性,实现了制造过程的定量分析,为复杂制造系统的建模和优化提出了一种新的方法。更多还原

【Abstract】 Manufacturing process was hard to be controlled quantitatively due to its dynamic changes. Therefore, an integrated computation intelligence approach was proposed for complex multi-objective optimization manufacturing process. Artificial Neural Network (ANN) was used for system modeling, which searched fitness function and target function value for Genetic Algorithms (GAs). And GAs was applied in multi-objective optimization. This approach was validated through application in high speed wired electro-discharge machining process, the results demonstrated the effectiveness and feasibility of this method. It realized quantitative analysis for manufacturing process, and provided a new method for modeling and optimization of complicated manufacturing processes.更多还原