不确定环境下多目标原材料采购问题研究

摘要

In order to reduce the procurement cost,increase the profit and improve the product quality of enterprises,strengthen the supply-chain management and enhance the competitiveness of enterprises in the process of the entire supply-chain,raw materials procurement with quantity discount under uncertain environment is studied.The objective of establishing the model is to minimize the total cost and the expected number of total defective materials and maximize the level of low-carbon of suppliers.The demand for each material are assumed to be uncertain variables but more practical.While a dynamic programming-based particle swarm optimization algorithm (DP-based PSO) is developed to solve the model.Finally a numerical example is conducted to test the effect of the proposed method and the algorithm.The results indicate that the proposed model can reduce the purchase cost,improve the quality of procurement and low carbon level of suppliers,and provide guidance for raw materials procurement.%为降低材料采购成本、提高企业利润、增强企业产品质量、增强企业供应链管理和增强企业在整个供应链中的竞争力,针对不确定需求下带有数量折扣的多目标原材料采购问题,结合国内外关于材料采购问题的研究现状,以采购成本最小、残次品数最少和供应商低碳化水平最高为目标建立数学模型,模型将原材料需求设置为不确定变量,更加贴近实际.运用基于动态规划的粒子群改进算法对模型求解,为提高算法运行效率,采用基于动态规划的编码方式,通过数值算例和算法对比验证了模型和算法的有效性,计算结果表明所建模型和所用算法能够有效地降低材料采购成本、提高采购质量和提高供应商的低碳化水平.