摘要
针对食品供应链加工环节召回优化问题,给出4层批次分散模型,包含原料、部件、半成品、成品4个层次和分解、组合、包装3个加工流程。该批次分散模型的求解是一个NP难度问题。提出一种基于人工蜂群算法的召回优化方法,并引入惩罚函数,将约束问题转化成无约束问题。仿真结果和性能对比表明,该算法收敛较快,运算开销小,可以显著降低平均召回规模,适用于食品供应链加工环节的召回优化。
In recent years,the traceability in food supply chain has been recognized as an essential tool for guaranteeing food safety and food quality. In this paper,a 4-level batch dispersion model,referring to the food batch dispersion model,is given to minimize the quantity of recalls. This model consists of four levels,respectively raw materials,components,semi-finished products and finished products while the model involves three operations,i, e. , disassembling,assembling and packaging. Since the 4-level batch dispersion is a NP hard problem,an artificial bee colony （ABC） algorithm is adopted to minimize the quantity of recalls to optimize traceability in food supply chain. Compared with the traditional intelligent optimization method,the ABC algorithm is proposed to maintain a balance between the global search ability and the local search ability, and to overcome the main disadvantage of the poor global search ability and local optimums. The simulation results show that the performances of the ABC algorithm can minimize the potential recalls quantity efficiently,which is applicable to the optimization of recall in food supply chain.
出处
《江南大学学报（自然科学版）》
CAS
2015年第2期166-171,共6页
Joural of Jiangnan University (Natural Science Edition)
基金
江苏省产学研前瞻性联合研究项目(BY2013015-04)
中央高校基本科研业务费专项资金项目(JUSRP31106)
关键词
追溯
召回
食品供应链
批次分散
人工蜂群算法
traceability, recall, food supply chain, batch dispersion, artificial bee colony algorithm
