Cross-docking centre operation optimization using simulation-based genetic algorithm

Abstract

The operational improvement of cross-docking centres in the literature involves job scheduling, layout design and dock assignment. The mentioned research is mainly concerned with makespan, number of tardy jobs or travel distance. However, these measures may not fully represent the main advantages of cross-docking operations. Little has been done to optimize the major performance measures of a cross-docking centre, which substantiates the main advantages of cross-docking technology. In this paper, inventory holding cost, transportation cost and backorder penalty cost are aggregated into total cost and a solution framework has been developed by integrating simulation, genetic algorithm (GA) and smart computing budget allocation (SCBA) for a comprehensive total cost minimization problem. This problem has huge search space even for medium-sized problem scenarios. To address this difficulty, the framework employs simulation to estimate the total cost, GA to search for better design and SCBA to efficiently allocate the simulation budget. Numerical experiments show that the proposed framework operates effectively in cases of different problem scales.