In a world of time slots, dynamic compartments and truck types, finding routes with an optimal sequences of pickup and delivery stop daily for all trucks is a big puzzle.

Given all the constraints (timeslots, capacity) and data (customers/shipments/legs) on a daily basis, how can you create the optimal routes including the stop sequences?

How can an advanced analytics model support in generating optimal routes in seconds allowing for quick calculations on different scenario’s routes and implemented in the day of operation?

The logistic chains between ports and hinterland locations are characterized by limited transparency, inefficiency and unclear choices for onward transportation. Making the right onward modality choice depends on a myriad of factors, and making the best decision can be quite challenging. This is when the idea of Synchromodality comes into play for your supply chain. With the right Synchromodal solution in place, planners are put in a position to make the best SCP&O decisions every time based on KPI’s.

Planning in a Synchromodal network involves geographical expertise & the ability to easily access all relevant planning information – in practice, this ability is often lacking. Ideally, planning involves multi-modal transportation from origin to destination. Due to a large number of planning variables, the optimal solution is highly dependent on soft, heuristic knowledge of expert planners & the availability of scattered, diffuse planning information.

When different transport modalities are handled by disparate planning processes and tools, planners cannot easily get a quick and accurate overview of all planning processes. This leads to  ineffective decision making and increased cost.

Despite the richness of information housed within a TMS system, information is not readily available for the planner to quickly optimize a plan and respond to “What-if” scenarios and/or changes in planning needs. This forces planners to rely on soft knowledge to address planning challenges.

In the complex intermodal chain, many actors and resources are involved. Real-time information is available and this puts increased pressure on planners. Intermodal companies must then invest in decision support to enable the planner to handle the complexity of today’s network options.

With the ever increasing importance of optimization of resource utilization, we chose the Advanced Planning & Scheduling solution, provided by Ab Ovo, to digitize our intermodal capacity planning.

Ab Ovo’s Synchromodal Solution processes all needed transport information for optimum planning scenarios, resulting in emission reduction & high cost savings.