考虑采购成本与组合风险的构件优化选择方法

An Optimization Model for System Component Selection to Minimize Cost and Combinational Risk

本文围绕着采购成本和组合风险这两个重要的系统非功能需求,将构件选择问题定义为在满足系统需求的情况下,为各模块选择具体的实施构件,实现系统总体设计最优。针对所建立的双目标整数规划模型,结合麦克劳林展开式二阶拉格朗日余项,给出了精确的关于系统组合风险预测的误差分析方法,据此得出应用该模型估计系统总体风险的适用条件。进一步设计了求解全部有效解集的启发式算法。并对由小到大四种规模的算例,采用衡量多目标优化算法的重要指标——生成有效解向量的比率(ONVGR),比较了本文提出算法与NSGA-II算法。

In contrast to the traditional process of product development,Component-Based Development(CBD)focuses on building products by integrating previously-existing components.So to start with,an available set of components should be identified.In this paper,this major problem of component-based system development involves the effective evaluation and selection alternative system components is addressed by considered the cost and combinational risk factors.Based on a bi-objective 0-1 integer programming,an optimization model is proposed that can assist decision-makers in selecting system components for minimizing cost and combinational risk,and satisfying system requirements.The condition of application of the proposed model is further proposed based on the Maclaurin expansion with second order Lagrange remained term.To solve the model efficiently,a supported efficient solution based algorithm is presented that can find the entire set of efficient solutions.Computational experience also describes in solving the problems using the Metaheuristics and the proposed algorithm.