With the popularity of mobile internet and the rise of Pinduoduo's "group purchase discount" business, community group buying has become a popular choice for online shopping among people. Community group buying achieves bulk purchases of goods through online reservations and offline delivery, reducing product prices and providing consumers with affordable prices. The community group buying point selection proposed in this thesis can effectively reduce delivery distances, lower costs, and provide competitive advantages for enterprises. At the same time, optimizing the logistics distribution path of agricultural products can effectively reduce distribution costs, shorten delivery times, and significantly increase logistics distribution profits. Therefore, research and implementation of community agricultural product group buying point optimization and distribution path planning systems have important theoretical and practical value. Based on the local community group buying needs in S City and comprehensive research from both domestic and international sources, this thesis focuses on the research of community group buying point selection and distribution path optimization. In terms of group buying point selection, choosing a more optimal solution helps to reduce overall delivery distances and service costs. Additionally, the optimization of agricultural product distribution paths is closely related to costs, time, and profits. Finally, this thesis designs a graphical user interface for a well-performing group buying point and path optimization simulation system to meet practical needs. In summary, the work of this thesis is mainly divided into three parts.
(1) To address the issue of community group buying node selection, this thesis proposes a novel chaotic Boltzmann sparrow search algorithm (CBSSA), which effectively reduces the delivery distance and service costs of community group buying node selection solutions. Additionally, this thesis designs a new community group buying node selection model, taking into account real-world location conditions and the service costs of community group buying nodes. Subsequently, this thesis builds a testing environment for optimizing community group buying node selection using MATLAB software, and compares the proposed algorithm with classical genetic algorithm methods. Experimental results demonstrate that, across multiple experimental scenarios, CBSSA reduces the delivery distance and service costs by at least 5.9% and 11.65%, respectively, compared to traditional genetic algorithms. This indicates that the CBSSA community group buying node selection method proposed in this thesis effectively reduces delivery distance and service costs.
(2) To address the problem of agricultural product distribution path planning, this thesis proposes a novel Quantum Ant Colony Optimization (QACO) algorithm, which effectively reduces delivery costs and time while increasing economic profits. Additionally, a new agricultural product distribution path planning model is designed in this thesis, along with a novel evaluation function. Furthermore, various experimental scenarios are set up to compare QACO with the latest improved Ant Colony Optimization (MACO), Variable Neighborhood Search Ant Colony Optimization (VNS-ACO), and classical Ant Colony Optimization (ACO) algorithms. Results show that, in a scenario with 30 community group buying points, QACO outperforms MACO, VNS-ACO, and classical ACO algorithms by at least 5.68% in economic profits and reduces delivery time by at least 17.09% while lowering delivery costs by at least 12.31%. These findings indicate that the proposed agricultural product path planning method effectively reduces delivery costs and time while increasing economic profits.
(3) Based on the above two important models and optimization algorithms, this thesis utilized the MATLAB App Designer platform to construct a graphical user interface for simulating the optimization of community agricultural product group buying points and the planning of distribution paths. The system includes login interface, community group buying node selection interface, and logistics path distribution planning interface. Finally, to verify the reliability of the system, comprehensive system functionality testing was conducted, and all designed functions of the system were effectively demonstrated.
谷歌
火狐
