Resource assignment and scheduling based on a two-phase metaheuristic for cropping system

This paper proposes a resource assignment and scheduling based on a two-phase metaheuristic for a long-term cropping schedule. The two-phase metaheuristic performs the optimization of resources assignment and scheduling based on a simulated annealing (SA), a genetic algorithm (GA) and a hybrid Petri nets model. The initial and progressive states of farmlands and resources, moving sequence of machinery, cooperative work, and deadlock removal have been well handled in the proposed approach. In the computational experiment, the schemes of emphasizing the resource assignment optimization, initializing the population of the GA with chromosomes sorted by the waiting time, and inheriting the priority list from tasks in the previous resources assignment improved the evolution speed and solution quality. The simulated result indicated that the formulated schedule has a high ratio of resource utilization in sugarcane production. The proposed approach also contributes a referential scheme for applying the metaheuristic approach to other crop production scheduling.