Performance Analysis of Three Intelligent Algorithms on Route Selection of Fishbone Layout

Li Zhou, Zhaochan Li, Ning Shi, Shaohua Liu and Ke Xiong
Additional contact information
Li Zhou: School of Information, Beijing Wuzi University, Beijing 101149, China
Zhaochan Li: School of Information, Beijing Wuzi University, Beijing 101149, China
Ning Shi: School of Information, Beijing Wuzi University, Beijing 101149, China
Shaohua Liu: School of Information, Beijing Wuzi University, Beijing 101149, China
Ke Xiong: School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China

Sustainability, 2019, vol. 11, issue 4, 1-17

Abstract: The Internet of Things (IoT) has become an important strategy in the current round of global economic growth and technological development and provides a new path for the intelligent development of the logistics industry. With the development of the economy, the demand for logistics benefits is becoming more important. The appropriate use of technologies related to IoT to improve logistics efficiency, such as cloud computing, mobile computing and data mining, has become a topic of considerable research interest. Picking operations are currently an extremely important and cumbersome aspect of logistics center tasks. To shorten the picking distance and improve work efficiency, this paper uses the genetic algorithm, ant colony algorithm and cuckoo algorithm to optimize the picking path in a fishbone-layout warehouse and establishes an optimized model of the warehouse picking path under the fishbone layout. Data-mining technology is used to simulate the model and obtain the simulation data under the condition of multiple orders. The results provide a theoretical basis for the study of the fishbone-layout picking path model and has certain practical significance for the efficient operation of logistics enterprises. Through optimization, it is conducive to the sustainable development of enterprises and to achieving long-term profitability.

Keywords: ant colony algorithm; cuckoo algorithm; fishbone layout; genetic algorithm; path optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/4/1148/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/4/1148/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:4:p:1148-:d:208035

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().