摘要
为解决ASP平台下动态联盟由于外部环境的复杂性导致的风险控制困难的问题,通过TOPSIS方法找到最优方案和最劣方案作为免疫遗传算法的抗原输入,每种应对方案作为抗体输入,计算抗原和抗体之间的亲和度从而找出接近最优方案的解。免疫遗传算法采用实数编码,把各种风险的应对措施用实数编码表示,通过变异和交叉操作产生下一代的抗体,保持了个体的先进性,提高了计算速度与精度;TOPSIS方法解决了免疫遗传算法中抗体在染色体群中浓度过高导致寻优过程早熟收敛的问题并且提高运算速度。风险控制模型的建立使得ASP平台下的动态联盟企业可用最低成本来达到有效地预防控制各种风险的目的。
To solve the question of risk control difficult of dynamic alliance based on the ASP for the complexity of the external environment,we found the optimal and the worst schemes as the antigen input of immune genetic algorithm through the TOPSIS method.Each solution was inputted as antibody to calculate correlating between antigen and antibody in order to find the optimal solution.Immune genetic algorithm utilizes real number coding,which can keep the advancement of next-generation antibodies that were produced by mutation and crossover operation.It improveed the calculation speed and accuracy.TOPSIS method solved the problem of optimization process premature convergence for antibody excessive concentrations in chromosomes by immune genetic algorithm.Construction risk control model makes that dynamic alliance enterprises based on the ASP can achieve the purpose of prevention and control various risks in least-cost.
出处
《制造技术与机床》
CSCD
北大核心
2011年第7期136-140,共5页
Manufacturing Technology & Machine Tool
基金
国家"863"高技术研究发展计划资助项目(2006AA04Z130)
国家自然科学基金资助项目(50475185
50575047)