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Abstract:
Recently, with the deterioration of the environment, increasing companies choose horizontal cooperation to achieve the goal of reducing environmental pollution and cost in the urban distribution industry. However, companies worry that the business information is leaked in the process of horizontal cooperation. This kind of mistrust often leads to the failure of horizontal cooperation. The emergence of blockchain technology has become a great means to resolve trust problem between partners, which ensures data sharing and trust through peer-to-peer, consensus mechanism and encryption technology. In response, this study proposes architecture of blockchain-based urban distribution system for horizontal cooperation that analyzes the components and layers of the urban distribution. Meanwhile, a smart contract, the innovative applications of blockchain, is designed to match the resource of supply and demand to design the distribution routes in the urban distribution system. To achieve the above goal, an open vehicle routing model of urban distribution taking into account environmental pollution factors is developed as the mathematical logic of smart contract, which aims at the lowest total cost including fixed, fuel, penalty, carbon emission and pollutant emission costs. Furthermore, the genetic algorithm is developed to support the implementation of smart contract, and the effectiveness of the smart contract is verified through a real case. This study narrows the knowledge gap in applying blockchain technology to urban distribution, and has brought contributions to the fields of blockchain and urban distribution. Finally, the limitation and future research direction are discussed.
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RESOURCES CONSERVATION AND RECYCLING
ISSN: 0921-3449
Year: 2022
Volume: 176
1 3 . 2
JCR@2022
1 3 . 2 0 0
JCR@2022
ESI Discipline: ENVIRONMENT/ECOLOGY;
ESI HC Threshold:47
JCR Journal Grade:1
CAS Journal Grade:1
Cited Count:
WoS CC Cited Count: 19
SCOPUS Cited Count: 22
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 8
Affiliated Colleges: