In this study,we introduce an integrated schedule of order picking and delivery for instant delivery.Order picking,including order batching and picking sequencing,is scheduled online under real-time order arrival,whic...In this study,we introduce an integrated schedule of order picking and delivery for instant delivery.Order picking,including order batching and picking sequencing,is scheduled online under real-time order arrival,which integrates order delivery by depicting order location dispersion in an online order picking strategy.Order delivery,including delivery person assignment and route planning,is modeled to minimize the total duration of order fulfillment by considering the influence of the order picking completion time.A rule-based online order picking strategy is established,and a customized ant colony optimization(ACO)algorithm is proposed to optimize order delivery.Experiments on 16 simulated instances of different scales demonstrate that our online order picking schedule considering order delivery outperforms existing approaches and that the customized ACO algorithm for order delivery is effective.展开更多
In the large-scale Distributed Virtual Environment(DVE)multimedia systems,one of key challenges is to distributedly preserve causal order delivery of messages in real time.Most of the existing causal order control app...In the large-scale Distributed Virtual Environment(DVE)multimedia systems,one of key challenges is to distributedly preserve causal order delivery of messages in real time.Most of the existing causal order control approaches with real-time constraints use vector time as causal control information which is closely coupled with system scales.As the scale expands,each message is attached a large amount of control information that introduces too much network transmission overhead to maintain the real-time causal order delivery.In this article,a novel Lightweight Real-Time Causal Order(LRTCO)algorithm is proposed for large-scale DVE multimedia systems.LRTCO predicts and compares the network transmission times of messages so as to select the proper causal control information of which the amount is dynamically adapted to the network latency variations and unconcerned with system scales.The control information in LRTCO is effective to preserve causal order delivery of messages and lightweight to maintain the real-time property of DVE systems.Experimental results demonstrate that LRTCO costs low transmission overhead and communication bandwidth,reduces causal order violations efficiently,and improves the scalability of DVE systems.展开更多
基金supported by the National Natural Science Foundation of China(72032001,71972071)the Ministry of Education,Humanities and Social Sciences Research Planning Foundation(21YJA630057).
文摘In this study,we introduce an integrated schedule of order picking and delivery for instant delivery.Order picking,including order batching and picking sequencing,is scheduled online under real-time order arrival,which integrates order delivery by depicting order location dispersion in an online order picking strategy.Order delivery,including delivery person assignment and route planning,is modeled to minimize the total duration of order fulfillment by considering the influence of the order picking completion time.A rule-based online order picking strategy is established,and a customized ant colony optimization(ACO)algorithm is proposed to optimize order delivery.Experiments on 16 simulated instances of different scales demonstrate that our online order picking schedule considering order delivery outperforms existing approaches and that the customized ACO algorithm for order delivery is effective.
基金This research work is supported by Hunan Provincial Natural Science Foundation of China(Grant No.2017JJ2016)Hunan Provincial Education Science 13th Five-Year Plan(Grant No.XJK016BXX001)+3 种基金Social Science Foundation of Hunan Province(Grant No.17YBA049)2017 Hunan Provincial Higher Education Teaching Re-form Research Project(Grant No.564)Scientific Research Fund of Hunan Provin-cial Education Department(Grant No.16C0269 and No.17B046)The work is also sup-ported by Open foundation for University Innovation Platform from Hunan Province,China(Grand No.16K013)and the 2011 Collaborative Innovation Center of Big Data for Finan-cial and Economical Asset Development and Utility in Universities of Hunan Province.We also thank the anonymous reviewers for their valuable comments and insightful sug-gestions.
文摘In the large-scale Distributed Virtual Environment(DVE)multimedia systems,one of key challenges is to distributedly preserve causal order delivery of messages in real time.Most of the existing causal order control approaches with real-time constraints use vector time as causal control information which is closely coupled with system scales.As the scale expands,each message is attached a large amount of control information that introduces too much network transmission overhead to maintain the real-time causal order delivery.In this article,a novel Lightweight Real-Time Causal Order(LRTCO)algorithm is proposed for large-scale DVE multimedia systems.LRTCO predicts and compares the network transmission times of messages so as to select the proper causal control information of which the amount is dynamically adapted to the network latency variations and unconcerned with system scales.The control information in LRTCO is effective to preserve causal order delivery of messages and lightweight to maintain the real-time property of DVE systems.Experimental results demonstrate that LRTCO costs low transmission overhead and communication bandwidth,reduces causal order violations efficiently,and improves the scalability of DVE systems.
