Fodder, Grain, Livestock & Timber
Improving efficiency in distribution within agriculture and forestry
Distribution in the agricultural and forestry sector contains many elements and types of transportation; bulk, packaged goods, odd size equipment, unhandy tree trunks, etc. In addition, some transportation tasks involve multiple legs and various transportation modes. Therefore, the type of transportation determines the needs regarding the planning type i.e. master route planning, dynamic route optimization, real-time route execution and route re-planning.
Moreover, the type of transportation determines the demands regarding the planning logic i.e. one leg versus multiple legs, transportation modes, forecasting and measuring, load planning, etc.
AMCS Route Planner and Fleet Planner
AMCS Route Planner and Fleet Planner are the ideal IT systems for planning and optimisation of all types of transportation in the agricultural and forestry industry. The solutions consist of various elements with functionality, which can be configured to cover exactly the needs of the customer. This means that customers can for example choose to have the system implemented with the purpose of only optimising master routes or only performing dynamic planning and execution.
Different planning needs
AMCS Route Planner has a powerful engine for optimising master routes, inserting customer and ad hoc orders into existing master routes and for daily batch-based route optimisation. These capabilities are especially relevant for distribution of for instance goods and fodder to a well-defined group of customers and/or outlets.
AMCS Fleet Planner supports dynamic and real-time-based optimisations, which can perform either batch or incremental planning. For incremental planning, the system will continuously change and re-optimise plans as orders are received, as well as re-optimize routes in real time based on GPS and status messages from a mobile system. These capabilities are especially relevant for companies with customers, which have a fluctuating demand for deliveries. For instance, this could be companies whose deliveries are based on forecasting of stock values or companies with numerous existing customers and many new customers, all with unpredictable orders.