Using an artificial neural network and a mathematical model for sugarcane harvesting scheduling

In this paper, the sugarcane harvesting scheduling problem, in the northeast region of Thailand, is addressed. Since there are many small size farmers are participated as suppliers of the sugarcane mill, a harvesting schedule, which could provide the maximum production yield for sugarcane mill and also equal opportunity for farmers to harvest at their suitable time are required. A model, which is the combination of an artificial neural network (ANN) and a mathematical model, is proposed to solve the problem. The ANN is used to forecast sugarcane yield of each plantation over harvesting season. Then, the forecasted values are used by the mathematical model to find the optimal harvesting schedule. The objective function of the proposed mathematical model is to maximize the total sugarcane yield; meanwhile the harvesting scheduling maintains the equality among farmers in the group. The application of the model is also investigated with an example problem.