Harvester scheduling joint with operator assignment

Socialized service of agricultural machinery has been considered an effective and convenient method for rural households in developing countries. While the concept of socialized service of agricultural machinery has the potential to improve agricultural production efficiency, there are new operational challenges. The many heterogeneous demands, operators and harvesters, and their complex matching relationships require novel methodologies for agricultural machinery service organizations to deal with the machine and staff scheduling. The traditional harvest scheduling problem has not considered operators' driving skills. Different operators have different driving skills of different types of harvesters, and different harvesters have different working abilities. Thus, it is necessary to assign high skill level operators to these harvesters that can work at more farmlands. This study addresses a harvester scheduling problem joint with operator assignment simultaneously. A mixed integer linear programming model is proposed to formulate our problem with the objective of minimizing the total working time and costs by determining the combinations of harvesters and operators and the routes of harvesters. Valid inequalities were derived for tightening the lower bounds after LP relaxation, which enables quickly solving problems of realistic size with near-optimal solutions. The responding heuristic algorithms are also developed. Computational studies were conducted to demonstrate the effectiveness and efficiency of our solution methodology and obtain managerial insights.