基于TOC和IA的能力受限产品组合优化

Capacity-constrained product mix optimization based on theory of constraints and immune algorithm

针对现有产品组合优化研究仅考虑自制资源能力限制、未考虑外包资源能力限制的问题,建立了能力受限产品组合优化的数学模型,并进行了模型分析和比较,得出了能力受限模型优化解的特征,为进一步构建仿生算法奠定了基础。应用免疫算法和约束理论构建了仿生算法——IA_TOC_Ⅲ,通过相应变通处理可用IA_TOC_Ⅲ算法求解考虑自制/外包情形的所有模型。通过对单/多瓶颈算例的仿真,IA_TOC_Ⅲ仿生算法在合理时间内得到了大、小规模产品组合决策的优化解。通过与已有算法的比较,验证了本模型和算法的有效性和实用性。

Current studies on product mix optimization didn＇t consider constrained capacity of outsourcing vendors but only focused on constrained capacity of self-manufacturer.To deal with this problem,a mathematical model for capacity-constrained product mix optimization was constructed.Model analysis and comparison were conducted and the characteristics of optimum solution to capacity-constrained model were obtained.It laid foundation for constructing biological algorithm.Based on Immune Algorithm（IA） and Theory of Constraints（TOC）,an intelligent search approach named IA_TOC_Ⅲ was proposed to search for optimum solution.Moreover,some transformation rules were given and IA_TOC_Ⅲ was generalized to solve all kinds of product mix optimization problems considering either manufacturing or outsourcing mode.Through simulation experiments,IA_TOC_Ⅲ was implemented to solve the small-scale and large-scale product mix optimization cases in reasonable time.Comparing IA_TOC_Ⅲ with other existing approaches,the feasibility and effectiveness of IA_TOC_Ⅲ was proved.