- 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: | XUE Feng, LIU Yongbo, HU Zuoan, CHEN Yifei. Railcar Traffic Distribution and Route Optimization Model Based on Dynamic Penalty Function[J]. Journal of Southwest Jiaotong University, 2022, 57(5): 941-948, 959. doi: 10.3969/j.issn.0258-2724.20210226
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In order to solve the constraint difficulty in the railway traffic distribution and route optimization model, and the inadequacy of swarm intelligence algorithm, a constraint optimization method based on penalty function is proposed. First, a virtual arc is set on the basis of the basic model of traffic distribution and route optimization, and the arc segment capability constraints in the model are relaxed by adding a penalty term to the objective function. Meanwhile, a dynamic update strategy is designed for the penalty intensity and penalty factor of the penalty term. Then, the improved grey wolf algorithm (IGWO) is applied to the solution of traffic distribution and route optimization models. Finally, combined with the road network data in a certain area, the models and algorithms before and after improvement are compared and analyzed. The results of case study show that, compared with the model before improvement, after introducing the penalty term, IGWO can find feasible solutions that satisfy the arc capacity constraints within a limited range; compared with the grey wolf algorithm (GWO), the distribution scheme calculated by IGWO reduces the average detour rate of the OD (origin-destination) cargo flow and the total cargo kilometers by 2.6% and 5.2%, respectively.
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