With the rapid growth of the e-commerce and the increasing awareness of environmental protection, retailers are facing new challenges to make product delivery fast and green while maintaining their profit margin. A balance between service level and cost to serve is required on both strategic and operational level. Transactional transportation decisions are usually made with transportation cost minimization as a target, due to the inefficiency of information flow in the organization. In this capstone project, we introduced a practical model to perform transactional route and load planning through quantifying the business implication of shipment delay. Export container consolidation for DC by-pass in import distribution was the use case, and analysis was performed on the historical shipment data from a global sports brand. Mixed Integer Linear Programming was used to model the problem based on the routes in the existing network. Total cost minimization was the objective. Carbon emissions for line-haul movements and delivery performance were included as planning effectiveness indicators. 30% total cost reduction and 13% improvement on delivery performance were seen with the sample data. The model is very efficient for transactional planning purpose, with 80% of the runs executed within 1 second. It is also scalable to simulate various business scenarios. We expect the findings provide directions to drive product and solution development.