Research on Production Plant Layout Optimization Based on Improved Genetic Annealing Algorithm
Research on Production Plant Layout Optimization Based on Improved Genetic Annealing Algorithm
复制标题
DOI：
10.4156/ijact.vol4.issue5.40
复制
发表时间：
2012-03
期刊：
影响因子：
--
通讯作者：
Kunpeng Yu;Yu Yang;Jingbo Guo;Tao Yang
中科院分区：
文献类型：
--
作者：
Kunpeng Yu;Yu Yang;Jingbo Guo;Tao Yang
建立了车间面积最小化、物流成本和非物流成本最优的多目标数学模型。在此基础上提出了一种改进的遗传退火算法。根据约束条件，引入初始种群和自适应参数，动态调整交叉和变异概率，有效防止早熟收敛和最优染色体的破坏。最后，通过对比分析表明，将研究结果应用于布局设计后，土地利用效率和生产效率都得到了提高。
A multi-objective (smallest workshop area, optimal logistics and non-logistics costs) mathematical model is built for the system layout design. Based on this model, an improved genetic annealing algorithm is proposed. According to the constraints, initial population and adaptive parameters are introduced to dynamically adjust crossover and mutation probability, which can effectively prevent premature convergence and the destruction of best chromosome. Finally, the comparative analysis shows the improved land use efficiency as well as production efficiency after applying the results to layout design.