- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | NI Shaoquan, LUO Xuan, XIAO Bin. Optimization of Vehicle–Cargo Matching Regarding Interests of Three Parties[J]. Journal of Southwest Jiaotong University, 2023, 58(1): 48-57. doi: 10.3969/j.issn.0258-2724.20210859
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To study the vehicle–cargo matching problem regarding the heterogeneous needs of the vehicle owner, cargo owner and platform under the platform mode, the platform demand is introduced given that the previous studies only consider the interests of both vehicle and cargo parties. Firstly, based on the analysis of the participant needs in the vehicle−cargo matching activity, a multi-objective optimization model is built to maximize the satisfaction of the delivery timeliness, minimize the freight cost and maximize the platform revenue. Secondly, in terms of model solution, the non-dominated sorting genetic algorithm Ⅱ (NSGA Ⅱ) with elite retention strategy is improved. On the one hand, elite selection coefficient is introduced in the process of updating the offspring population to improve the diversity of the population, and on the other hand, the adaptive idea is combined to adjust the probability of cross mutation in the algorithm iterations. Finally, the simulation experiments are carried out using the data of vehicles and freights in the areas of Chengdu and Chongqing. The results show that the accuracy of the improved algorithm proposed is more than 91% on small and medium-sized examples, and the average convergence speed is increased by about 45%, compared with the conventional NSGA Ⅱ algorithm. In terms of algorithm stability, the proposed algorithm is less affected by random initialization, and the relative standard deviation of multiple experiments is less than 1%.
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