TY - GEN
T1 - Multi-Objective Optimization Decision for Business Allocation on Blockchain
AU - Shangguan, Zizhuo
AU - Li, Donghe
AU - Yang, Qingyu
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The increasing adoption of blockchain technology in supply chain management has sparked widespread interest. However, collaborative order allocation led by enterprises in the chain still faces challenges, including efficiency, traceability and trust issues. In this paper, based on a multi-objective genetic algorithm, an order allocation model is proposed with the objective function of maximizing the interests of the chain owner enterprise (minimizing cost, maximizing efficiency, and maximizing service quality), maximizing the number of enterprises participating in the chain, and optimizing the stability of the blockchain. The optimal solution is determined by employing the TOPSIS decision-making method. Finally, simulation experiments are used to demonstrate the stability and validity of the model.
AB - The increasing adoption of blockchain technology in supply chain management has sparked widespread interest. However, collaborative order allocation led by enterprises in the chain still faces challenges, including efficiency, traceability and trust issues. In this paper, based on a multi-objective genetic algorithm, an order allocation model is proposed with the objective function of maximizing the interests of the chain owner enterprise (minimizing cost, maximizing efficiency, and maximizing service quality), maximizing the number of enterprises participating in the chain, and optimizing the stability of the blockchain. The optimal solution is determined by employing the TOPSIS decision-making method. Finally, simulation experiments are used to demonstrate the stability and validity of the model.
KW - Blockchain
KW - Multi-criteria Decision-making
KW - Multi-objective Genetic Algorithm
KW - Order Allocation
UR - https://www.scopus.com/pages/publications/85207440530
U2 - 10.1109/CCSSTA62096.2024.10691884
DO - 10.1109/CCSSTA62096.2024.10691884
M3 - 会议稿件
AN - SCOPUS:85207440530
T3 - Proceedings of 2024 IEEE 25th China Conference on System Simulation Technology and its Application, CCSSTA 2024
SP - 383
EP - 387
BT - Proceedings of 2024 IEEE 25th China Conference on System Simulation Technology and its Application, CCSSTA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024
Y2 - 21 July 2024 through 23 July 2024
ER -