Implications of the computational complexity of transit route network redesign for metaheuristic optimisation systems

Abstract

The transit route network design problem is a computationally intractable optimisation problem that seeks a set of bus routes and frequencies that minimises the operator cost while maximising passenger utility. Previous attempts to optimise this problem have used metaheuristic and heuristic techniques to find solutions that allow for a complete redesign of the transit network. In reality, however, a complete redesign of the network may encounter political resistance from existing transit users if the routes that they use are eliminated. Here, an intelligent agent optimisation system is used to optimise the transit route network redesign (TRNR) problem, which is subject to the additional constraint that existing routes in the network remain, although perhaps serviced with lower frequency. When applied to the transit network in Mumbai, India, the optimisation system found significant improvement in the route network, even when subject to these constraints. In a scenario in which the current routes were maintained with frequency of stops reduced by no more than 50%, operator cost could be improved by 18.1% while maintaining the current level of passenger utility. On the other hand, passenger utility could be improved by 5.5% at current levels of operator cost.

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