Optimisation for Integrated Service Planning and Operation

**Current approaches to fleet infrastructure planning focus predominantly on like-for-like replacement of vehicles (with infrastructure planning largely a second-order concern).** Our research indicates that for passenger and fleets services, this like-for-like replacement approach risks increasing the infrastructure needed by 25%, increasing overall infrastructure costs by a similar amount, increasing the likelihood of grid constraints and pushing up costs for consumers.

To overcome this challenge, instead of the like-for-like approach, three critical (but inter-related) problems need to be solved simulateneously. Our solution will solve problems together for the first time by building an ALM system and emulator based on hyperheuristic optimisation and AI.

The solution will then guarantee the lowest "total cost of infrastructure", delivering critical cost advantage to fleets and lower prices to service users.