Analysis of the Impact of Foreign Trade Policies on China’s Pet Food Industry Based on Particle Swarm Optimization
- DOI
- 10.2991/978-94-6463-958-2_15How to use a DOI?
- Keywords
- Particle swarm optimization; pet food; resource allocation optimization; foreign trade policy
- Abstract
This paper constructs a revenue-maximizing planning model to address the impact of foreign trade policy changes on China’s pet food industry, and solves it using the particle swarm optimization algorithm. The model optimizes resource allocation between domestic markets and major export destinations by constraining minimum distribution ratios in domestic markets and production capacity ceilings. Results show that the domestic market allocation will reach 805,000 tons in 2026, marking a significant increase in proportion. The United States and Europe remain primary export destinations with 522,000 tons and 472,000 tons respectively, while emerging markets such as Southeast Asia and Japan are gradually demonstrating potential. Through in-depth analysis of the current status and future trends of China’s and global pet food industries, a series of targeted recommendations are proposed.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Hanxue Liu PY - 2025 DA - 2025/12/26 TI - Analysis of the Impact of Foreign Trade Policies on China’s Pet Food Industry Based on Particle Swarm Optimization BT - Proceedings of the 5th International Conference on Management Science and Software Engineering (ICMSSE 2025) PB - Atlantis Press SP - 126 EP - 132 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6463-958-2_15 DO - 10.2991/978-94-6463-958-2_15 ID - Liu2025 ER -