Abstract:

Pre-cooling of agricultural production base is the biggest shortcoming in the whole cold chain logistics system of agricultural products in China. In the current context， establishing a comprehensive pre-cooling system and popularizing the application of rapid pre-cooling equipment are crucial tasks for the development of the full cold chain of agricultural products in our nation. The mobile precooling resource has the advantages of low input cost and high flexibility. It is helpful to reduce cost and improve efficiency to carry out scientific and reasonable resource allocation and operation path planning for mobile precooling resources. With a specific focus on the “first kilometer” mobile pre-cooling resource layout and operation path planning in villages and towns across China， a mixed integer mathematical programming model is formulated. This model simultaneously determines the site selection of mobile pre-cooling resource stopovers， the quantity distribution of mobile pre-cooling vehicles， and the multi-round-trip pre-cooling path planning for these vehicles. In light of the NP-hard， nonlinear， and multi-stage decision-making challenges inherent in the model， a rapid solution framework is further proposed. This framework combines the step search method， K-means cluster analysis technique， simulated annealing algorithm， and variable neighborhood search algorithm.The main research results are as follows　（1） With the increase of the example size， the proposed algorithm in this paper is superior to the traditional simulated annealing algorithm and local neighborhood search algorithm in terms of service cost and total cost， although it takes longer in calculation time， the gap is gradually narrowing. （2） Considering the round trip of vehicles can effectively reduce the total cost. When considering the round trip， the vehicle purchase cost and service cost are relatively high， but the total cost is also high； when not considering the round trip， the vehicle purchase cost is relatively high， but the service cost is relatively low， and the total cost is also low. （3） The sensitivity analysis shows that with the increase of the proportion of service cost in the total cost， the number of vehicle round trips and the number of vehicles increase； with the increase of the single maximum path value of the mobile pre-cooling vehicle， the number of vehicle round trips first decreases and then increases slightly， and the number of vehicles first decreases and then increases slightly； with the increase of the end time range and span of the time window， the number of vehicle round trips first increases slightly and then increases significantly， and the number of vehicles continues to increase； increasing the step length can save calculation time， but the total cost will be relatively worse.

Key words: mobile precooling resources, layout optimization, multiple round trip path planning, intelligent solution algorithm