An Improved Genetic Algorithm for the Multi-temperature Food Distribution with Multi-Station

This paper studies on the food distribution route planning problem for improving the customer satisfaction and the operator cost of food providers. In the first, the problem is formulated to a combinatorial optimization which is hard to be solved. Thus, a polynomial time algorithm is proposed to solve the problem, combining genetic algorithm and neighbourhood search, to increase the total amount of distributed food and reduce the distribution cost. The proposed algorithm employs the genetic al-gorithm with integer coding to decide the assignment of customers to distribution vehicles, and integrates the neighbourhood search strategy into the genetic algorithm to improve its performance. Experiment results show that the proposed method improved the distribution performance up-to 111.09%, 73.10% and 70.21%, respectively, in the distributed food amount, the cost efficiency, and the customer satisfaction.

@article{Wang2022,
  title     = {An Improved Genetic Algorithm for the Multi-temperature Food Distribution with Multi-Station},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {6},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Bo Wang and Jiangpo Wei and Bin Lv and Ying Song},
  doi       = {10.14569/IJACSA.2022.0130604},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130604}
}