为减少不必要的图书搬运和读者等待时间,以无人书店为研究对象,设定作业区中心点坐标为决策变量,在作业单元安全距离、作业区面积与整体面积关系、出入闸机通道限制等约束条件下,构建以图书搬运时间最短和作业区综合关系最大为目标的无人书店设施布局优化模型,以SLP法所得布局方案作为遗传算法初始解,在其交叉变异阶段引入模拟退火算法Metropolis接受准则,以此提出一种改进遗传算法进行求解。后以A无人书店为例,对比遗传算法、SLP+遗传方法、遗传模拟退火算法、改进遗传算法4种方法所得布局方案的图书搬运时间最优值、作业区综合关系值及目标函数最优值,结果表明改进遗传算法效果最优,所求得设施布局方案更为科学合理,有效节省读者订单完成时间,提升顾客购书阅读体验。
In order to reduce unnecessary book handling and readers' waiting time, this paper takes the unmanned bookstore as the research object, sets the coordinates of the centre point of the operation area as the decision variables, and constructs an unmanned bookstore facility layout optimization model with the goal of the shortest book handling time and the largest comprehensive relationship of the operation area under the constraints of the safety distance of the operation unit, the relation between the operation area area and the overall area, and the limitation of the access gate passageway, etc, and uses the SLP method as the initial solution for the layout scheme. The layout scheme obtained is used as the initial solution of the genetic algorithm, and a simulated annealing algorithm Metropolis acceptance criterion is introduced in its cross-variation stage to propose an improved genetic algorithm for solving. After taking an unmanned bookstore as an example, comparing the optimal value of book handling time, the value of the integrated relationship between operation areas and the optimal value of the objective function of the layout scheme obtained by the genetic algorithm, SLP+genetic method, genetic simulated annealing algorithm, and improved genetic algorithm, the results show that the improved genetic algorithm is the most effective, and the layout of the facilities obtained by the scheme is more scientific and reasonable, which can effectively save the time of completing readers' orders, and enhance the customers' book buying and reading experience. The results show that the improved genetic algorithm is optimal and the proposed facility layout scheme is more scientific and reasonable.
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