Intelligent Fleet Logistics

The Intelligent Fleet Logistics project commenced in June 2008 and is combining operations research algorithms for vehicle routing with the flexibility of constraint programming. This research is use inspired, being driven by real-world applications of the technology to deliver systems applicable to industry requirements. Our first commercial offering is a Transportation Management System that can better model the detail of client operations than current vehicle routing systems.

The Constraint Programming Platform project commenced in April 2004 and is developing a generic platform for optimisation. The Zinc modelling language efficiently represents complex combinatorial optimisation problems and is used by us as the flexible modelling component.

What will Intelligent Fleet Logistics Achieve?

A significant portion of the freight movement in Australia is provided by road freight. Road freight operators need to cope with fluctuating demands, changing deliveries and the varied operational constraints to efficiently manage their operation. A solution for Fleet Logistics needs to both accurately model their operation and provide saving through efficient automated planning.

We develop algorithms that are capable of modelling all aspects of transportation systems to optimise the allocation of resources to reduce cost.

Our initial software product is a Transportation Routing System designed to be integrated with existing client database and CRM software and configured to meet their exact transportation needs.

The key competitive advantages of our software solution are:

• The rapid configuration and modelling of the software to meet the clients business operation.
• More accurate and precise models lead to a more accurate and appropriate resulting set of routes for the client.
• The use of state-of-the-art optimisation and route planning technology derives more efficient schedules than current systems.

Who will benefit?

Fleet Logistics operators can anticipate a 10-30% saving through more efficient asset and resource utilisation. Automated planning of vehicles, crews, depots, cross-docking to reduce distance, time, fuel costs and CO2 emissions are key aims of our software.

Our end-users are any user of transportation operating a fleet of approx. 20 or more vehicles with a varied operational plan.

Key features:

Automated Vehicle Routing and Scheduling Solutions

• Operations Research Derived Routing Algorithms – vehicle routing and optimisation
• Constraint Programming Platform - technology base for complex constraint scheduling
• Precise Modelling – detailed, configurable, accurate, readily incorporates specifics
• Tackles Large and Complex Problems – through a new solver hybrid algorithm
• Immediate Tangible Benefits – saving per vehicle, crew, fuel, CO2 … real-time basis

for Automated Asset Utilisation in

• Transportation Management Systems – road, rail, shipping fleets in logistics services
• Supply Chain: Planning, Management & Execution – complex supply routes involving multiple modes of transport, processing and real-time changing demands

Progress:

We have completed a series of successful commercial engagements to optimise road transportation and their distribution networks. The analyses performed have included:

• Dynamic Route Planning: dynamic real-time operation of routes for transportation and service engineers
• Static Route Planning: develop a set of static routes to operate repeatedly
• Fleet Configuration: determine appropriate vehicle fleet automatically
• Routing and Crew Scheduling: determine efficient schedules for routes and crews incorporating their skills, availability etc
• Transportation Network Optimisation: schedule the transportation network determining cross-dock or delivery timings through modelling operations at the transportation level

The Transportation Routing System is now available and will continue further development to model new areas of transportation until the end of project in December 2015. 

 
Project Leader: Dr Andrew Verden

Project Team:

Prof. Toby Walsh

Dr Phil Kilby

Dr Olga Kuznetsova

Dr Adi Botea

Dr Will Uther

Mr Tony Arnold

Mr Kenneth Cruz

Mr Daniel Harabor

Mr Darryl Holmes

Mr Andrew Purchas