Enhancement for human resource management in the ULD buildup process of aircargo terminal: a strategic linkage approach This study proposes a strategic linkage method with mathematical model, simulation model and heuristic approaches to an adaptive workforce scheduling problem reflecting the work site situation of the air cargo terminal. For the application of the proposed method, we first generate an initial workforce schedule using the optimization model for minimizing labor costs. The simulation model is then used to verify that the initial schedule is applicable onsite. If the initial plan does not meet the service level expressed as a delay in the departure of aircrafts, by linking optimization and simulation models, additional required personnel are determined for reducing the frequency of departure delay. But, though the experiments, we were able to confirm that the linkage of optimization and simulation alone resulted in the creation of excess manpower. To compensate for the limitation of the linkage, we develop the Backward Removal Heuristics (BRHs) algorithm. In an experiment with BRHs algorithm, we showed that BRHs could reduce the number of unnecessarily added workers based on the interaction between utilization of workers and operation congestion. With case study on the ULD buildup process of K airline aircargo terminal, the linkage model with BRHs algorithm is tested and proven its effectiveness. The experimental results show that the workforce schedule from the linkage model increases the service level and the cost, but when applied to the BRHs algorithm, the model maintains the service level but decreases the cost.

An Efficient 2D Genetic Algorithm for Optimal Shift Planning Considering DailyWise Shift Formats: A Case of Airport Ground Staff Scheduling Owing to the computational efficiency in dealing with combinatorial optimization problems, the genetic algorithms (GAs) have been widely applied to human resource planning and scheduling. Shift planning is of particular importance for personnel scheduling when practical concerns must be taken into account. Dailywise shift formats are often introduced in practical operations in order to facilitate execution of the planned tasks and accommodate certain managerial convenience. However, the highly repetitive nature of running dailywise shift formats entails an extreme imbalance of set covering between the tasks and staff availability, which leads to tremendous computational challenges in solving the combinatorial optimization problem that is subject to large redundancy of zero elements. In line with the inherent twodimensions of shift planning in terms of shift formats and days, this paper proposes a twodimensional (2D) encoding scheme to implement the GA for efficient shift planning. An application to a reallife airport Ground Staff Scheduling (GSS) problem is presented to illustrate the feasibility and potential of the proposed 2D GA for efficient handling of dailywise shift formats.