Path Planning for Multiple AGV Systems Using Genetic Algorithm in Warehouse

DOI

10.2991/cimns-18.2018.24How to use a DOI?

Keywords

pathing planning; genetic algorithm; multiple AGV; optimization; warehouse

Abstract

Path planning problem in multiple automated guided vehicle (AGV) system has been proven to be NP-Hard problem by many researchers. This complex task is being done using various mathematical techniques traditionally. This paper proposes an optimal path planning method for the multiple AGV system based on genetic algorithm. The constraint in the optimization task is that, each AGV starts and returns to transfer center, travelling to a unique set of pick-up stations, each pick-up station is visited by exactly one AGV for goods picking up. The Cost Function is to search for the shortest path i.e. the least distance needed for each AGV to travel from the start location to individual points and back to the original starting place. The experimental results shows the solution in this paper is effective which provide a reference for practical applications.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chao Li
AU  - Chuqing Cao
AU  - Yunfeng Gao
PY  - 2018/11
DA  - 2018/11
TI  - Path Planning for Multiple AGV Systems Using Genetic Algorithm in Warehouse
BT  - Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018)
PB  - Atlantis Press
SP  - 106
EP  - 109
SN  - 2352-538X
UR  - https://doi.org/10.2991/cimns-18.2018.24
DO  - 10.2991/cimns-18.2018.24
ID  - Li2018/11
ER  -