Integrated operations planning in highly electrified container terminals considering time-of-use tariffs

With the electrification of port equipment, container terminals have become electricity-intensive consumers. The time-of-use (TOU) pricing policy has prompted container terminals to reopti-mize their operations planning to decrease electricity costs. However, it is an essential challenge to optimally plan highly correlated operations of a container terminal in response to TOU tariffs. Traditional operations planning of a container terminal focuses on improving operational efficiency under flat electricity tariffs. The obtained solution under flat electricity tariffs may be far from optimal when the TOU pricing policy is involved. To this end, this paper addresses an integrated operations planning problem from container terminals under TOU tariffs. In particular, several vital resources, including quay cranes, yard cranes, and berths, are jointly scheduled to handle tasks from vessels and external trucks. The objective is to minimize the total costs. We formulate the integrated optimization problem as a mixed-integer linear programming (MILP) model. We then propose a logic-based Benders decomposition (LBBD) algorithm for the problem. The proposed LBBD method uses valid inequalities to speed up the solution procedure. To address practical-sized instances, we design a tailored genetic algorithm (GA) with several acceleration techniques. We demonstrate the performance of the LBBD method and tailored GA through numerical experiments. Results indicate that the proposed integrated approach yields a better solution than its decentralized counterpart, demonstrating that the total operational cost can be significantly reduced by applying the developed model. We also discuss managerial implications drawn from our results for the integrated operations planning under TOU tariffs, which help port operators make critical decisions.