## 2 Related Literature
The paper [12] presented a wide overview of the modern management practices including a soil preparation, crop fertilization, proper irrigation, pest management, disease management and storage of potato crop using these technologies. The authors of [12] reviewed the environmental and economic aspects of the technology using major research engines including Science Direct, Scopus and Web of Sciences. They discuss the challenges faced by potato farmers in increasing yields, improving quality and reducing production costs. The use of yield monitoring systems, precision planting, variable rate application of inputs and remote sensing was discussed. They summarize the state of the art in precision agricultural technologies. The review [12] highlighted the benefits of using precision agricultural technologies in potato crop management. The paper [13] addresses the problem of assigning agricultural machines in multi-machine navigation. Agricultural machines need to complete multiple agricultural jobstogether. To realize the management of agricultural machinery cooperation, studies on job assignment based on the ant colony algorithm were conducted in [13]. A job assignment model of agricultural machinery cooperation was established by combining dynamic job assignments. A job assignment process based on the ant colony algorithm was established by considering the match between real supply and a real demand, the job capacity of the agricultural machinery, and the job cycle and cost. The dynamic and static job assignments of agricultural machinery cooperation based on the ant colony algorithm were realized on MATLAB. Based on the static job assignment, the dynamic job assignment was realized with different possible scenarios, including new jobs and malfunctioning harvesters, thus laying a foundation for solving the scheduling problem under a farmland job environment. In farmland operations, multiple agricultural machines complete multiple jobs together. In the paper [14], studies on path conflict detection based on topographic maps and time windows were conducted to solve the conflict-free path problem for agricultural machinery in a farmland environment. The path preplanning was performed based on a topographic map and the algorithm proposed by [PERSON]. The global path conflict was detected based on the given time windows. The global path conflict detection algorithm was simulated on MATLAB with the topographic map of Zhuozhou Farm (Chine). The computational results showed that the path optimization and path conflict detection of agricultural machinery can be realized based on the topographic map and time windows. A conflict resolution strategy requiring the least time was obtained to achieve a conflict-free path when using multiple agricultural machines. Farmers are faced with the problem of increasing yields with limited resources. The extensive use of agricultural machinery is one of the most efficient methods to achieve this. Since agricultural machinery is expensive, it is economically impractical for small-scale farmers. Instead, farmers can submit a usage request to an agricultural machinery company, and the company will dispatch their machines to farmers to provide an operational service. This business model has shown promising benefits. The authors of [15] developed a two-step dispatching algorithm for shared agricultural machinery for specified time windows. At the first step, a spatiotemporal clustering algorithm was used to cluster farmlands according to their location, time windows and crop strain. The shortest route within each given cluster of farmlands was also determined. At the second step, the shared agricultural machines were routed across the clusters to minimize the dispatching costs. Both these steps were formulated as a mixed-integer linear programming problem. The two-step heuristics based on CPLEX were proposed to solve the problem. Computational experiments were conducted with large data from a real-world agricultural machinery company.