Retail And E Commerce Industry
Travel And Transportation Industry
Truck routing optimization is a key component in the Supply Chain Optimization area. When truck routing optimization is well done, it can drive immense efficiencies of scale.
Traditionally, trucking companies focus on on-time delivery in the most cost-effective way.
While this is broadly the right focus, in reality many dynamic uncertainties and operational constraints like customer time windows, resource availabilities pose limits to such an optimization.
However, advances in technology today allow dynamic capacitated truck routing and optimization capabilities which open a whole new set of possibilities to add efficiency and delight the end customer keeping their SLAs intact .
By incorporating forecasting techniques especially during peak periods and generating various what-if scenarios, clients can be better prepared to handle the day of ops surprises or disruption scenarios.
ORMAE provides expert solutions in Route Planning and Optimization with planners able to visualize optimized route plans, perform mid to long term capacity planning through achievable sales target scenarios and drive efficiency and productivity by cost effective ways keeping the customer happy.
ORMAE worked on truck routing optimization problem with multiple depots and time windows for large scale retail industry client. Loading operation from warehouse as well as unloading operation at the customer can have its own time variability. Service time at each customer was dependent on order with some variability.
Challenges, Solution and Business Impact
1. Transit time between customers and depot to customer depends on traffic along with department of transportation restrictions.
2. As time variability in service time was dependent on order and it becomes even more challenging with the errors in data collection.
3. In some cases, truck might make multiple trips back and forth from depot within same day if delivery quantity at each customer is high but lower delivery time.
Customized route optimization algorithm addressing challenges of multi trips or single trips was developed by creating set of dummy locations and artificial transit times. Model was intelligently able to use set of transit times between pair of locations rather than unique transit time as transit time depended on time of departure.
Business Impact: Optimization algorithm was able to scientifically assign each customer location to warehouse and cut down total routing cost along with disruption handling ability. Currently, algorithm is going through implementation and testing stage.
Delivery Optimization with time windows
Multi-depot optimization balancing truck utilization
Operational constraints satisfaction on distance and times using Data science
Mid/Long term capacity planning to achieve revenue targets
Customized route optimization addressing challenges of multi trips and single trips
Optimal routings with multiple warehouses in different locations and customer SLAs with specified time windows.