MORe: Past Projects - Transport, Logistics and Supply Chain

Multi Modal Transportation and Logistics

In a highly successful project MORe developed an optimisation package to determine shipping routes and quantities for a leading Australian importer and distributor of agricultural products. The optimisation package determines the lowest cost sourcing plan while accounting for complex interactions between a series of influencing factors.

This project continues to deliver improved planning flexibility and substantial savings in planning time and sourcing costs for the client.

Logistics with Depots

Less-than-truckload transportation logistics is highly complex, with issues of consignment routing, load consolidation, vehicle routing and scheduling, and driver shift allocation all to be determined, and all interacting.  MORe has developed hybrid constraint programming methods to yield highly efficient and cost-effective solutions.

Transport Asset Management

Simulation and probability techniques were used to ensure a new (private) bus service deploys transport assets that achieves the desired quality of service, at minimum cost.

Supply Chain Optimisation and Facility Location for Recyclates

Economic recycling in regional Australia requires efficient transportation and the right structure for the supply (collection) chain.  A decision support tool was developed that allows Government to optimise trade-offs between sorting and transport costs.

Inventory Routing

New stochastic optimisation methods have been used to trade off the risk of customer shortage against re-supply costs when managing inventory at customer sites.

Military Vehicle Path Planning

Whether at sea, on land, in the air, or under-sea, military vehicles seek feasible paths through hostile terrain that minimize their risk of detection.  Planning such paths employs operations research techniques.

Emergency Vehicle Planning

Emergency vehicles, such as roadside assistance vehicles, must be able to respond quickly to requests for their services.  Deciding how many vehicles are needed, and where these should be stationed, to provide a given quality of service, is difficult given the unpredictable nature of the demand.  Hybrid constraint programming methods have been used to determine cost-effective, robust solutions for emergency vehicle operators.

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