Optimizing a transportation network requires planning and controlling many factors, including drivers, vehicles, and maintenance. This coordination is the responsibility of an operating team with the right planning tools, extensive knowledge about the transfer of goods, and processes for managing tight delivery schedules. With the right people and technology, a transportation network can be optimized.
Optimization of transportation network capacity is a critical element of transportation planning. The concept of network capacity is used in many transportation applications, including traffic control and road pricing. Other applications have focused on car ownership estimation and land-use optimization. Recent research has also addressed capacity flexibility and redundancy in transportation networks.
Capacity, price, and service optimization can help transportation companies meet their business objectives and remain profitable. It is essential to understand the factors that affect these decisions. Price and service elasticity affect revenue, business performance, and passenger satisfaction. Pricing is also an integral component of load balancing and capacity management. With the current economic downturn, transportation companies must reevaluate pricing practices.
A methodology for achieving consistent pricing optimization in a transportation network is described in FIG. 4. The method starts by building a network of O-D pairs based on the allowable detour ratio and the allowed betweenness ratio. Then, the optimization engine computes the optimal price for each O-D team.
Leveraging data for continuous improvement of a transportation network can be a highly effective method to reduce costs and improve customer satisfaction. Using data, transportation leaders can identify areas of waste, overlap, and large volumes that could be improved. This process is known as managed transportation.
Transportation route optimization is one of the most challenging mathematical problems to solve. It can take days to find the optimal solution, even for the most brilliant mathematicians. A model needs to account for all possible variables and multiple delivery points for optimal results. As the number of delivery points increases, the equation for vehicle routing becomes exponentially more complicated.
An Integrated SCMS for transportation network optimization combines strategic, tactical, and operational planning activities. It can optimize network layout based on multiple criteria, including geographic routing, customer grouping, vehicle loading and saturation, and costs. In addition, it generates optimized vehicle routes and schedules based on vehicle load factors and distances.
The transportation network is an area that can quickly spiral out of control and lead to cost overruns and supply chain disruptions. With a good transportation network, these problems can be eliminated. This is possible by using the best practices for network optimization. The key to success is improving visibility and the effectiveness of decision-making.
Earlier transportation planning relied on historical data only, but a fully integrated SCMS blends historical data with real-time input to provide the most accurate forecasts. Furthermore, it is smart enough to identify which historical information is relevant to a shipment and can limit its intake to only the relevant data.