The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the ...The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the balance of number of kinds of items between different zones but not the number of items and the idle time in each zone. In this paper, an idle factor is proposed to measure the idle time exactly. The idle factor is proven to obey the same vary trend with the idle time, so the object of this problem can be simplified from minimizing idle time to minimizing idle factor. Based on this, the model of item assignment problem in synchronized zone automated order picking system is built. The model is a form of relaxation of parallel machine scheduling problem which had been proven to be NP-complete. To solve the model, a taboo search algorithm is proposed. The main idea of the algorithm is minimizing the greatest idle factor of zones with the 2-exchange algorithm. Finally, the simulation which applies the data collected from a tobacco distribution center is conducted to evaluate the performance of the algorithm. The result verifies the model and shows the algorithm can do a steady work to reduce idle time and the idle time can be reduced by 45.63% on average. This research proposed an approach to measure the idle time in synchronized zone automated order picking system. The approach can improve the picking efficiency significantly and can be seen as theoretical basis when optimizing the synchronized automated order picking systems.展开更多
Food delivery has emerged as a crucial aspect of the dining experience,driven by the proliferation of the Internet and the expansion of the catering industry.Delivery times have become a significant factor affecting c...Food delivery has emerged as a crucial aspect of the dining experience,driven by the proliferation of the Internet and the expansion of the catering industry.Delivery times have become a significant factor affecting customer satisfaction.However,the inherent unpredictability of the delivery process can lead to delays,which in turn can diminish customer contentment with the delivery platform if the actual delivery time surpasses the promised time frame.Consequently,this paper addresses the optimization of delivery routes for couriers who encounter uncertainty during their deliveries.To quantify the randomness of the distribution process,the study introduces a random influence factor that accounts for road obstacles and weather conditions.Different coefficients for road obstruction and weather influence are assigned to various road sections and delivery times to accommodate the stochastic nature of static road segments.Based on this,a takeout delivery optimization model that incorporates stochastic elements is formulated.This model is designed to effectively optimize the delivery plan,achieving a balance between delivery costs and customer satisfaction.The proposed model is solved using a taboo search algorithm.The effectiveness of the delivery model and algorithm is validated through simulations that compare the performance of the delivery route model under different weather conditions and road obstacle coefficients.The objective of this study is to assist delivery couriers in planning their routes in a rational and scientific manner to enhance delivery efficiency while managing the uncertainty of the road network.Additionally,the research aims to provide practical recommendations and solutions to reduce delivery operation costs and improve customer satisfaction.展开更多
基金Supported by Independent Innovation Foundation of Shandong University of China(Grant No.2013GN007)
摘要The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the balance of number of kinds of items between different zones but not the number of items and the idle time in each zone. In this paper, an idle factor is proposed to measure the idle time exactly. The idle factor is proven to obey the same vary trend with the idle time, so the object of this problem can be simplified from minimizing idle time to minimizing idle factor. Based on this, the model of item assignment problem in synchronized zone automated order picking system is built. The model is a form of relaxation of parallel machine scheduling problem which had been proven to be NP-complete. To solve the model, a taboo search algorithm is proposed. The main idea of the algorithm is minimizing the greatest idle factor of zones with the 2-exchange algorithm. Finally, the simulation which applies the data collected from a tobacco distribution center is conducted to evaluate the performance of the algorithm. The result verifies the model and shows the algorithm can do a steady work to reduce idle time and the idle time can be reduced by 45.63% on average. This research proposed an approach to measure the idle time in synchronized zone automated order picking system. The approach can improve the picking efficiency significantly and can be seen as theoretical basis when optimizing the synchronized automated order picking systems.
基金supported by the National Natural Science Foundation of China(Grant No.U2141234)by grants from the National Key Research and Development Program of China(2021YFB2600300).
摘要Food delivery has emerged as a crucial aspect of the dining experience,driven by the proliferation of the Internet and the expansion of the catering industry.Delivery times have become a significant factor affecting customer satisfaction.However,the inherent unpredictability of the delivery process can lead to delays,which in turn can diminish customer contentment with the delivery platform if the actual delivery time surpasses the promised time frame.Consequently,this paper addresses the optimization of delivery routes for couriers who encounter uncertainty during their deliveries.To quantify the randomness of the distribution process,the study introduces a random influence factor that accounts for road obstacles and weather conditions.Different coefficients for road obstruction and weather influence are assigned to various road sections and delivery times to accommodate the stochastic nature of static road segments.Based on this,a takeout delivery optimization model that incorporates stochastic elements is formulated.This model is designed to effectively optimize the delivery plan,achieving a balance between delivery costs and customer satisfaction.The proposed model is solved using a taboo search algorithm.The effectiveness of the delivery model and algorithm is validated through simulations that compare the performance of the delivery route model under different weather conditions and road obstacle coefficients.The objective of this study is to assist delivery couriers in planning their routes in a rational and scientific manner to enhance delivery efficiency while managing the uncertainty of the road network.Additionally,the research aims to provide practical recommendations and solutions to reduce delivery operation costs and improve customer satisfaction.