IAES International Journal of Robotics and Automation (IJRA)
Vol 6, No 2: June 2017

A Guided Ant Colony Optimization Algorithm for Conflict-free Routing Scheduling of AGVs Considering Waiting Time

Li Junjun (Shanghai Maritime University)
Xu Bowei (Shanghai Maritime University)
YANG Yongsheng (Shanghai Maritime University)
Wu Huafeng (Shanghai Maritime University)



Article Info

Publish Date
01 Jun 2017

Abstract

Efficient conflict-free routing scheduling of automated guided vehicles (AGVs) in automated logistic systems can improve delivery time, prevent delays, and decrease handling cost. Once potential conflicts present themselves on their road ahead, AGVs may wait for a while until the potential conflicts disappear besides altering their routes. Therefore, AGV conflict-free routing scheduling involves making routing and waiting time decisions simultaneously. This work constructs a conflict-free routing scheduling model for AGVs with consideration of waiting time. The process of the model is based on calculation of the travel time and conflict analysis at the links and nodes. A guided ant colony optimization (GACO) algorithm, in which ants are guided to avoid conflicts by adding a guidance factor to the state transition rule, is developed to solve the model. Simulations are conducted to validate the effectiveness of the model and the solution method.

Copyrights © 2017






Journal Info

Abbrev

IJRA

Publisher

Subject

Automotive Engineering Electrical & Electronics Engineering

Description

Robots are becoming part of people's everyday social lives and will increasingly become so. In future years, robots may become caretaker assistants for the elderly, or academic tutors for our children, or medical assistants, day care assistants, or psychological counselors. Robots may become our ...