孙浩. 基于遗传算法的再制造逆向物流网络随机选址模型[J]. 信息与控制, 2009, 38(2): 223-228,233.
引用本文: 孙浩. 基于遗传算法的再制造逆向物流网络随机选址模型[J]. 信息与控制, 2009, 38(2): 223-228,233.
SUN Hao. A Stochastic Location Model for Remanufacturing Reverse Logistics Network Based on Genetic Algorithm[J]. INFORMATION AND CONTROL, 2009, 38(2): 223-228,233.
Citation: SUN Hao. A Stochastic Location Model for Remanufacturing Reverse Logistics Network Based on Genetic Algorithm[J]. INFORMATION AND CONTROL, 2009, 38(2): 223-228,233.

基于遗传算法的再制造逆向物流网络随机选址模型

A Stochastic Location Model for Remanufacturing Reverse Logistics Network Based on Genetic Algorithm

  • 摘要: 针对再制造逆向物流网络不确定性高的特点,建立了一个混合整数非线性规划(mixed integer nonlinear programming,MINLP)的随机选址模型.模型中将回收中心和再制造工厂分别看作具有M/M/l和M/M/c特征的随机排队系统,考虑了废旧产品在系统中的逗留时间和库存费用.然后提出一种双层遗传算法进行求解:用外层遗传算法搜索0-1整型变量的可行组合,用内层遗传算法解决剩余的运输子问题.最后通过一个算例说明了模型和算法的有效性.

     

    Abstract: Based on the characteristic of high uncertainty in remanufacturing reverse logistics networks,a stochastic location model for mixed integer nonlinear programming(MINLP) is built,in which return centers and remanufacturing factories are seen as stochastic queuing systems that are of characteristics of M/M/l and M/M/c respectively.Cycle time and inventory costs of the old products in the system are taken into account.Then a bi-level genetic algorithm is proposed.The feasible combinations of 0-1 binary variables are searched by the outer genetic algorithm and the remaining transportation sub-problems are solved by the inner genetic algorithm.Finally,an example is given to prove the validity of the model and algorithm.

     

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