摘要
通过分析生物体新陈代谢的生理机能,建立人工代谢算法模型。通过分析底物和生成物之间的浓度差建立多步催化反应动力学模型。通过对城市网络和代谢网络进行类比,建立基于浓度差的TSP问题寻优模型。实例推导表明,人工代谢算法能有效地实现TSP问题的寻优规划。
Artificial metabolic algorithm(AMA) model was built based on physiological metabolic functions in orgarnsin, Multi-step catalytic reaction kinetics model was obtained by analysis concentration difference between substrate and product. Searching optimization model for traveling salesman problem(TSP) based on concentration difference was established by using analogous analysis between city network and metabolic network. One real example states that optimization programming for traveling salesman problem(TSP) can be implemented efficiently through artificial metabolic algorithm.
出处
《计算机科学》
CSCD
北大核心
2010年第7期195-199,242,共6页
Computer Science
基金
国家杰出青年科学基金项目(60425310)资助
关键词
人工代谢算法
TSP问题
代谢算子
酶
Artificial metabolic algorithm(AMA),Traveling salesman problem(TSP), Metabolic operator, Enzyme