产品设计方案费效权衡的随机机会约束规划模型

针对产品设计方案费效权衡中由于未考虑生产过程中不确定性因素影响而导致的权衡结果易产生偏差的问题, 提出将不确定优化理论引入产品设计方案费效权衡模型中。在对关键设计参数敏感性分析的基础上，将敏感性变量以及费用估算的偏差描述为随机变量，构建基于以产品设计方案费效权衡的随机机会约束规划模型，并采用嵌入蒙特卡洛模拟的遗传算法求解，得到考虑不确定因素影响的最优产品设计方案。最后以混凝土泵车为实例，验证了模型的有效性。研究表明，采用费效权衡随机机会约束规划模型得到的产品设计方案,更能反映生产实际，可以最大程度保证不确定条件下产品设计决策目标的实现。

Stochastic chance-constrained programming of product design cost-effective trade-off

The uncertainty problems in the production process often affected the result of cost-effective trade-offs for product design scheme. To solve this problem, this paper introduced uncertainty optimization theory to the decision-making of cost-effective trade-offs. Considering uncertainty problems of the production process in the decision-making of product design scheme, and on the basis of sensitivity analysis of key performance parameters, the paper described the sensitivity variables and cost estimates deviation as random variables, and then built the stochastic chance-constrained programming model. Then the paper obtained the optimal solution with Monte Carlo simulation combined genetic algorithm (MCS-GA). In the end, through an example with the concrete pump truck, the results show that the design program traded-off with stochastic programming model can better reflect the actual production, so the product design targets of under uncertain conditions can be achieved at the maximum extent.