Cell-Based Local Search Heuristics for Guide Path Design of Automated Guided Vehicle Systems With Dynamic Multicommodity Flow
This article discusses the guide path design of automated guided vehicle (AGV) systems for which we propose a model that incorporates a dynamic multicommodity flow with capacity constraints from a pickup to a delivery point. The problem is formulated as the selection of a guide path connecting a giv...
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Veröffentlicht in: | IEEE transactions on automation science and engineering 2020-04, Vol.17 (2), p.966-980 |
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description | This article discusses the guide path design of automated guided vehicle (AGV) systems for which we propose a model that incorporates a dynamic multicommodity flow with capacity constraints from a pickup to a delivery point. The problem is formulated as the selection of a guide path connecting a given set of pickup/delivery points. A cell-based local search that is based on an original neighborhood technique is developed. In the proposed method, the guide path is effectively optimized based on a local search of cell-based neighborhood search preserving connectivity constraints and the subsequent solution of a dynamic multicommodity flow problem. The performance of the proposed method is strengthened by the redundant elimination of arcs and intensification of search according to the concept of the flow-concentrated cell. The effectiveness of the proposed method is demonstrated by comparing it with a general-purpose solver and recent algorithms for fixed-charge capacitated multicommodity network design problems. A real case study is presented to demonstrate the applicability of the proposed method by using simulation software. Note to Practitioners -Due to the recent growth of online shipping, the design of automated warehousing systems is receiving much attention. Most automated warehousing systems introduce multiple automated guided vehicles (AGVs) for transportation. This article presents an efficient optimization of guide path design considering congestions and dynamic multicommodity flow routing. We develop cell-based local search heuristics for the guide path design problem for AGV systems that can be applied to a large-scale transportation model to solve the problem efficiently. Our major finding is that the guide path design with the dynamic multicommodity flow can significantly reduce the delays caused by congestions and improve the efficiency of the warehousing systems. The effectiveness of the derived guide path design is evaluated by simulation software. The feasibility of the guide path is confirmed in several case studies. |
doi_str_mv | 10.1109/TASE.2019.2952920 |
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The problem is formulated as the selection of a guide path connecting a given set of pickup/delivery points. A cell-based local search that is based on an original neighborhood technique is developed. In the proposed method, the guide path is effectively optimized based on a local search of cell-based neighborhood search preserving connectivity constraints and the subsequent solution of a dynamic multicommodity flow problem. The performance of the proposed method is strengthened by the redundant elimination of arcs and intensification of search according to the concept of the flow-concentrated cell. The effectiveness of the proposed method is demonstrated by comparing it with a general-purpose solver and recent algorithms for fixed-charge capacitated multicommodity network design problems. A real case study is presented to demonstrate the applicability of the proposed method by using simulation software. Note to Practitioners -Due to the recent growth of online shipping, the design of automated warehousing systems is receiving much attention. Most automated warehousing systems introduce multiple automated guided vehicles (AGVs) for transportation. This article presents an efficient optimization of guide path design considering congestions and dynamic multicommodity flow routing. We develop cell-based local search heuristics for the guide path design problem for AGV systems that can be applied to a large-scale transportation model to solve the problem efficiently. Our major finding is that the guide path design with the dynamic multicommodity flow can significantly reduce the delays caused by congestions and improve the efficiency of the warehousing systems. The effectiveness of the derived guide path design is evaluated by simulation software. The feasibility of the guide path is confirmed in several case studies.</description><identifier>ISSN: 1545-5955</identifier><identifier>EISSN: 1558-3783</identifier><identifier>DOI: 10.1109/TASE.2019.2952920</identifier><identifier>CODEN: ITASC7</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Automated guided vehicles ; Automated guided vehicles (AGVs) ; Automation ; Autonomous vehicles ; block layout ; Computer simulation ; Design optimization ; dynamic multicommodity flow ; flow path design ; Heuristic algorithms ; heuristics ; Layout ; Mathematical model ; Routing ; Search problems ; Searching ; Software ; System effectiveness ; Transportation ; Vehicle dynamics</subject><ispartof>IEEE transactions on automation science and engineering, 2020-04, Vol.17 (2), p.966-980</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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The problem is formulated as the selection of a guide path connecting a given set of pickup/delivery points. A cell-based local search that is based on an original neighborhood technique is developed. In the proposed method, the guide path is effectively optimized based on a local search of cell-based neighborhood search preserving connectivity constraints and the subsequent solution of a dynamic multicommodity flow problem. The performance of the proposed method is strengthened by the redundant elimination of arcs and intensification of search according to the concept of the flow-concentrated cell. The effectiveness of the proposed method is demonstrated by comparing it with a general-purpose solver and recent algorithms for fixed-charge capacitated multicommodity network design problems. A real case study is presented to demonstrate the applicability of the proposed method by using simulation software. Note to Practitioners -Due to the recent growth of online shipping, the design of automated warehousing systems is receiving much attention. Most automated warehousing systems introduce multiple automated guided vehicles (AGVs) for transportation. This article presents an efficient optimization of guide path design considering congestions and dynamic multicommodity flow routing. We develop cell-based local search heuristics for the guide path design problem for AGV systems that can be applied to a large-scale transportation model to solve the problem efficiently. Our major finding is that the guide path design with the dynamic multicommodity flow can significantly reduce the delays caused by congestions and improve the efficiency of the warehousing systems. The effectiveness of the derived guide path design is evaluated by simulation software. The feasibility of the guide path is confirmed in several case studies.</description><subject>Algorithms</subject><subject>Automated guided vehicles</subject><subject>Automated guided vehicles (AGVs)</subject><subject>Automation</subject><subject>Autonomous vehicles</subject><subject>block layout</subject><subject>Computer simulation</subject><subject>Design optimization</subject><subject>dynamic multicommodity flow</subject><subject>flow path design</subject><subject>Heuristic algorithms</subject><subject>heuristics</subject><subject>Layout</subject><subject>Mathematical model</subject><subject>Routing</subject><subject>Search problems</subject><subject>Searching</subject><subject>Software</subject><subject>System effectiveness</subject><subject>Transportation</subject><subject>Vehicle dynamics</subject><issn>1545-5955</issn><issn>1558-3783</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kF1LwzAUhosoOKc_QLwJeN2Zj6ZtLufchzBR2NTLkCZnLqNdNGmRXvjfbd3w6hw4z_seeKLomuARIVjcrcer6YhiIkZUcCooPokGhPM8ZlnOTvs94TEXnJ9HFyHsMKZJLvAg-plAWcb3KoBBS6dViVagvN6iBTTehtrqgDbOo3ljDaAXVW_RAwT7sUdug8ZN7SpVd9G_s0FvsLW6BLRqQw1VQO-259u9qqxGT03Z1bmqcsbWLZqV7vsyOtuoMsDVcQ6j19l0PVnEy-f542S8jDUVrI51YkSW69SkCkhBKVClU0IVEUYbyHShU6oyjDnNEsgSo1SR8IIw3bNaJ2wY3R56P737aiDUcucav-9eSsrynGCa8Z4iB0p7F4KHjfz0tlK-lQTL3rLsLcvesjxa7jI3h4wFgH8-F4ymmLJfEdB6MA</recordid><startdate>20200401</startdate><enddate>20200401</enddate><creator>Nishi, Tatsushi</creator><creator>Akiyama, Shuhei</creator><creator>Higashi, Toshimitsu</creator><creator>Kumagai, Kenji</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Note to Practitioners -Due to the recent growth of online shipping, the design of automated warehousing systems is receiving much attention. Most automated warehousing systems introduce multiple automated guided vehicles (AGVs) for transportation. This article presents an efficient optimization of guide path design considering congestions and dynamic multicommodity flow routing. We develop cell-based local search heuristics for the guide path design problem for AGV systems that can be applied to a large-scale transportation model to solve the problem efficiently. Our major finding is that the guide path design with the dynamic multicommodity flow can significantly reduce the delays caused by congestions and improve the efficiency of the warehousing systems. The effectiveness of the derived guide path design is evaluated by simulation software. 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subjects | Algorithms Automated guided vehicles Automated guided vehicles (AGVs) Automation Autonomous vehicles block layout Computer simulation Design optimization dynamic multicommodity flow flow path design Heuristic algorithms heuristics Layout Mathematical model Routing Search problems Searching Software System effectiveness Transportation Vehicle dynamics |
title | Cell-Based Local Search Heuristics for Guide Path Design of Automated Guided Vehicle Systems With Dynamic Multicommodity Flow |
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