An optimization model and its algorithm of bulk grain transportation with time windows

In this paper, a bulk gram transportation problem with time windows is proposed and solved. It is too idealistic and impractical for traditional transportation model to apply because of ignoring shipping time. This paper applies probability and statistics in order to convert transportation time that is not within the time windows into penalty cost, thus formulating a multi-objective model with two goals: (1) minimize the traditional transportation cost and (2) minimize the penalty cost if delayed or ahead of time. A solution algorithm for the optimization model is also proposed and case analysis shows that this proposed model is capable of providing a optimum solution within a short computation time. Managerial insights on bulk gram transportation and gram supply chain governance, especially on the coordination mechanism between gram depots and gram processing companies are drawn.