4.7 Article

The two-echelon multi-trip vehicle routing problem with dynamic satellites for crop harvesting and transportation

期刊

APPLIED SOFT COMPUTING
卷 77, 期 -, 页码 387-398

出版社

ELSEVIER
DOI: 10.1016/j.asoc.2019.01.040

关键词

Memetic algorithm; Two-echelon routing; Dynamic satellite; Harvesting and transportation

资金

  1. MOE (Ministry of Education in China) Liberal Arts and Social Sciences Foundation [18YJC630070]
  2. Nanjing Agricultural University Fundamental Research Funds for the Central Universities [SKYZ2018031]

向作者/读者索取更多资源

The harvesting and transportation system involves a harvest scheduling and a transportation plan. The grain, harvested by combine-harvesters, is then transported by transporters from disperse farmlands to the depot. The spot where combine-harvesters transfer wheat to transporters is dynamic because the location of these spots correspond with combine-harvesters' work. In this paper, the harvesting and transportation problem is considered as a two-echelon multi-trip vehicle routing problem with a dynamic satellite (2E-MTVRPDS) because the combine-harvester is used multiple times in the planning horizon and the transporter is used multiple times in a work day. The mixed integer linear programming model is proposed based on the features of the problem. This work presents an optimum solution with a heuristic algorithm. The dynamic satellite is transferred as the static case in the heuristic. The computational experiments are constructed to test the performances of the proposed algorithm. Five instances with different sizes are adopted to test the stability of the algorithm. The calculation deviation of testing instances is acceptable. On one hand, the optimal effectiveness can be achieved when the number of instances is less than 200. With the increase in the number of instances, the optimal efficiency declines. On the other hand, the optimal solution appears to have a time window of 0.2 h in all instances with different sizes. This study provides a decision model for agricultural production to implement optimal harvesting operations. (C) 2019 Elsevier B.V. All rights reserved.

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