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Genetic Scheduling and Reinforcement Learning in Multirobot Systems for Intelligent Warehouses
Joint Authors
Dou, Jiajia
Yang, Pei
Chen, Chunlin
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-29
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
A new hybrid solution is presented to improve the efficiency of intelligent warehouses with multirobot systems, where the genetic algorithm (GA) based task scheduling is combined with reinforcement learning (RL) based path planning for mobile robots.
Reinforcement learning is an effective approach to search for a collision-free path in unknown dynamic environments.
Genetic algorithm is a simple but splendid evolutionary search method that provides very good solutions for task allocation.
In order to achieve higher efficiency of the intelligent warehouse system, we design a new solution by combining these two techniques and provide an effective and alternative way compared with other state-of-the-art methods.
Simulation results demonstrate the effectiveness of the proposed approach regarding the optimization of travel time and overall efficiency of the intelligent warehouse system.
American Psychological Association (APA)
Dou, Jiajia& Chen, Chunlin& Yang, Pei. 2015. Genetic Scheduling and Reinforcement Learning in Multirobot Systems for Intelligent Warehouses. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074241
Modern Language Association (MLA)
Dou, Jiajia…[et al.]. Genetic Scheduling and Reinforcement Learning in Multirobot Systems for Intelligent Warehouses. Mathematical Problems in Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1074241
American Medical Association (AMA)
Dou, Jiajia& Chen, Chunlin& Yang, Pei. Genetic Scheduling and Reinforcement Learning in Multirobot Systems for Intelligent Warehouses. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074241
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074241