Cross-docking assessment and optimization using multi-agent co-simulation: a case study

Abstract

Cross-docking is an operation where incoming freights from trucks or trains are directly loaded onto outbound trucks or trains to distributors, theoretically eliminating the need for interim storage warehouses. It is widely used throughout the retail industry to reduce supply chain related costs. In this paper, a cross-docking feasibility and optimization case study, based on a simulation model framework, is presented. The simulation model framework is created using the hybrid of discrete-event and agent-based model, allowing accurate and customized description of suppliers, distributors, and the cross-dock. The simulation model framework was used to assess the feasibility of implementing cross-docking operation for a global manufacturing firm’s technical consumer product supply chain and to optimize the cross-docking performance within established constraints. Controllable input parameters were evaluated for their impact to key cross-docking metrics and optimized for best cross-docking operation performances. Analysis and optimization results are presented with recommendations.