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Optimization for medical logistics robot based on model of traveling salesman problems and vehicle routing problems
International Journal of Advanced Robotic Systems ( IF 2.3 ) Pub Date : 2021-06-18 , DOI: 10.1177/17298814211022539
Hui Jin 1, 2 , Qingsong He 1 , Miao He 1, 3 , Shiqing Lu 1 , Fangchao Hu 1, 2 , Daxian Hao 3
Affiliation  

Fast medicine dispensing system (FMDS) as a kind of medical logistic robot can dispense many drugs for one prescription at the same time. To guarantee the sustainability of drug dispensation, it is required that FMDS replenish drugs rapidly. The traditional order picking model (OPM) is difficult to meet the demand of prompt replenishment. To solve the problems of prolonged refilling route and inefficiency of drugs replenishment, a mixed refilling model based on multiple steps traveling salesman problem model (MTSPM) and vehicle routing problem model (VRPM) is proposed, and it is deployed in two circumstances of FMDS, including temporary replenishment mode (TRM) and concentrate replenishment mode (CRM). It not only meted the demand under different circumstances of drug replenishment but also shortened the refilling route significantly. First, the new pick sets were generated. Then, the orders of pick sets were optimized and the new paths were achieved. When the number of pickings is varied no more than 20, experiment results declared that the refilling route is the shortest by utilizing MTSPM when working under the TRM condition. Comparing MTSPM with OPM, the rate of refilling route length decreased up to 32.18%. Under the CRM condition, the refilling route is the shortest by utilizing VRPM. Comparing VRPM with OPM, the rate of refilling route length decreased up to 58.32%. Comparing VRPM with MTSPM, the rate of refilling route length has dropped more than 43.26%.



中文翻译:

基于旅行商问题和车辆路径问题模型的医疗物流机器人优化

快速配药系统(FMDS)作为一种医疗物流机器人,可以同时为一个处方配药。为了保证配药的可持续性,需要FMDS快速补药。传统的订单拣选模式(OPM)难以满足及时补货的需求。为解决补给路线延长、补药效率低下的问题,提出了一种基于多步旅行商问题模型(MTSPM)和车辆路径问题模型(VRPM)的混合补给模型,并在FMDS的两种情况下进行部署,包括临时补货模式(TRM)和浓缩补货模式(CRM)。不仅满足了不同情况下的补药需求,而且大大缩短了补药路线。第一的,生成了新的拾取集。然后,优化拾取集的顺序并实现新路径。当采摘次数变化不超过20次时,实验结果表明,在TRM条件下工作时,利用MTSPM的再填充路径最短。MTSPM 与 OPM 相比,重新填充路径长度的比率下降了 32.18%。在CRM条件下,利用VRPM补给路线最短。VRPM与OPM相比,补料路径长度下降58.32%。VRPM 与 MTSPM 相比,路由长度的重新填充率下降了 43.26% 以上。实验结果表明,在 TRM 条件下工作时,使用 MTSPM 的再填充路径最短。MTSPM 与 OPM 相比,重新填充路径长度的比率下降了 32.18%。在CRM条件下,利用VRPM补给路线最短。VRPM与OPM相比,补料路径长度下降58.32%。VRPM 与 MTSPM 相比,路由长度的重新填充率下降了 43.26% 以上。实验结果表明,在 TRM 条件下工作时,使用 MTSPM 的再填充路径最短。MTSPM 与 OPM 相比,重新填充路径长度的比率下降了 32.18%。在CRM条件下,利用VRPM补给路线最短。VRPM与OPM相比,补料路径长度下降58.32%。VRPM 与 MTSPM 相比,路由长度的重新填充率下降了 43.26% 以上。

更新日期:2021-06-18
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