关键词: 静态知识化制造环境, 自进化, 滚动时域, 双层遗传算法, 两阶段算法

Abstract:

For an aircraft engine assembly workshop under static knowledgeable manufacturing environment, the self-evolution problem of knowledgeable manufacturing systems was studied. Rolling horizon method was adopted to implement the assembly workshop's periodic self-evolution. On the basis of the characteristics of the problem, a mathematical model of the static sub-problem at each decision moment was established. A rolling rule was proposed based on the initial decision scheme, and a two-phase algorithm was given to solve the self-evolution problem. For the mathematical model, a BiGA was proposed. Finally, simulation results demonstrate that the proposed model and algorithms are effective and feasible. The influences of the sizes of rolling window and rolling step on the production performance were also analyzed.

Key words: static knowledgeable manufacturing environment, self-evolution, rolling horizon, bi-level genetic algorithm(BiGA), two-phase algorithm