In an era where people in the world are concerned about environmental issues, companies must reduce distribution costs while minimizing the pollution generated during the distribution process. For today’s multi-depot problem, a mixed-integer programming model is proposed in this paper to minimize all costs incurred in the entire transportation process, considering the impact of time-varying speed, loading, and waiting time on costs. Time is directional; hence, the problems considered in this study are modeled based on asymmetry, making the problem-solving more complex. This paper proposes a genetic algorithm combined with simulated annealing to solve this issue, with the inner and outer layers solving for the optimal waiting time and path planning problem, respectively. The mutation operator is replaced in the outer layer by a neighbor search approach using a solution acceptance mechanism similar to simulated annealing to avoid a local optimum solution. This study extends the path distribution problem (vehicle-routing problem) and provides an alternative approach for solving time-varying networks.

Pork accounts for a high proportion of the Chinese population’s meat consumption, and imported pork is heavily traded, reducing supply of domestic pork in the face of continued demand. Global pork markets are becoming more competitive, riding the wind of the bilateral free trade agreement. The World Food and Agriculture Organization (FAO) compiles prices for other major food categories but does not track changes in the imported pork prices in China. This study has filled this gap by designing the Imported Pork Producer Declaration Price Index (PPI_IPD). Using the well-known Producer Price Index (PPI) model, PPI_IPD is based on the data from Chinese customs import declarations, which has high reliability and reasonableness. For this reason, the index can help governments, enterprises, analysts, and others to conduct analysis for imported pork prices in China and avoid international trade risks. The findings show that proposed PPI_IPD is highly correlated with the Chinese domestic pork market and the pork price industry stock market. The index helps monitor changes in international pork prices and is an effective tool for analyzing and controlling trade risks.