MULTI-OBJECTIVE STOCHASTIC SIMULATION-BASED OPTIMISATION APPLIED TO SUPPLY CHAIN PLANNING
提出一种结合随机离散事件仿真与多目标优化的两阶段方法，用于解决化工制造企业的多级供应链规划问题，数值实验证明了该方法的优势。
The paper discusses the optimisation of complex management processes, which allows the reduction of investment costs by setting the optimal balance between product demand and supply. The systematisation of existing methods and algorithms that are used to optimise complex processes by linking stochastic discrete-event simulation and multi-objective optimisation is given. The two-phase optimisation method is developed based on hybrid combination of compromise programming, evolutionary computation and response surface-based methods. Approbation of the proposed method is performed on the multi-echelon supply chain planning problem that is widely distributed in industry and its solution plays a vital role in increasing the competitiveness of a company. Three scenarios are implemented to optimise supply chain tactical planning processes at the chemical manufacturing company based on using different optimisation methods and software. The numerical results prove the competitive advantages of the developed two-phase optimisation method.