In the context of Industry 4.0 and based on the demand of digital logistics construction of industrial enterprises, this paper integrates the concept of digital twin into Refined Logistics Supply Chain construction. Considering the constraints of multi-distribution center, heterogeneous vehicle performance, distribution cost, quasi-shipment certificate and humanized management, Refined Logistics Supply Chain System (RLSCS) and cross-regional scheduling optimization model of logistics vehicles with multidistribution center were established. The designed model can minimize the transportation cost, reduce the transportation time, and improve the vehicle load rate. An adaptive elite honey badger target algorithm based on cubic mapping mechanism (IHBA), is designed to solve the model. Further, performance evaluation by optimizing test functions, the convergence performance of IHBA algorithm was demonstrated. Finally, the simulation experiment is carried out according to the actual business data and it is compared to eight other optimistic algorithms. The experimental results show that the proposed algorithm is more effective and more robust, and the related models and algorithms can provide research basis for industrial products digital supply chain system.INDEX TERMS Industry 4.0, refined supply chain, multi-objective constraint, logistics distribution, honey badger algorithm, cubic mapping mechanism.
Heterogeneous UAVs performing patrol tasks are a new type of border patrol method with high flexibility, high patrol efficiency, and low operating cost In order to improve the ability of heterogeneous UAVs to perform border patrol task, by constructing a three-dimensional complex coordinated planning model, a multi-objective fitness function with the minimum patrol energy consumption and maximum patrol coverage of UAVs in a complex mountain environment is established. Design an improved shuffled frog leaping algorithm (ISFLA) based on spiral search mechanism to solve the problem of task planning in complex mountain environment. The proposed algorithm is verified by simulation experiments. The simulation results show that the ISFLA algorithm for solving the path problem in complex three-dimensional environment has significantly improved the solving efficiency, accuracy and global convergence compared with the particle swarm optimization (PSO), differential evolution (DE) and shuffled frog leaping algorithm (SFLA). The experiments show that the proposed algorithm also has excellent solving ability in solving complex planning problems.
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