Routing Optimization of Intelligent Vehicle in Automated Warehouse | Zendy

Yancong Zhou | Zendy; Yongfeng Dong | Zendy; Hong-mei Xia | Zendy; Junhua Gu | Zendy

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Routing Optimization of Intelligent Vehicle in Automated Warehouse

Author(s) -

Yancong Zhou,

Yongfeng Dong,

Hong-mei Xia,

Junhua Gu

Publication year - 2014

Publication title -

discrete dynamics in nature and society

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.264

H-Index - 39

eISSN - 1607-887X

pISSN - 1026-0226

DOI - 10.1155/2014/789754

Subject(s) - ant colony optimization algorithms , computer science , routing (electronic design automation) , obstacle , convergence (economics) , vehicle routing problem , key (lock) , population , mathematical optimization , warehouse , artificial intelligence , mathematics , computer network , business , computer security , demography , marketing , sociology , political science , law , economics , economic growth

Routing optimization is a key technology in the intelligent warehouse logistics. In order to get an optimal route for warehouse intelligent vehicle, routing optimization in complex global dynamic environment is studied. A new evolutionary ant colony algorithm based on RFID and knowledge-refinement is proposed. The new algorithm gets environmental information timely through the RFID technology and updates the environment map at the same time. It adopts elite ant kept, fallback, and pheromones limitation adjustment strategy. The current optimal route in population space is optimized based on experiential knowledge. The experimental results show that the new algorithm has higher convergence speed and can jump out the U-type or V-type obstacle traps easily. It can also find the global optimal route or approximate optimal one with higher probability in the complex dynamic environment. The new algorithm is proved feasible and effective by simulation results

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