Genetic algorithm for biobjective urban transit
routing problem
Publication date
2013
Creators
Abstract
This paper considers solving a biobjective urban transit routing problem with a genetic algorithm approach. The objectives are to
minimize the passengers’ and operators’ costs where the quality of the route sets is evaluated by a set of parameters. The proposed
algorithm employs an adding-node procedure which helps in converting an infeasible solution to a feasible solution. A simple
yet effective route crossover operator is proposed by utilizing a set of feasibility criteria to reduce the possibility of producing an
infeasible network. The computational results from Mandl’s benchmark problems are compared with other published results in the
literature and the computational experiments show that the proposed algorithm performs better than the previous best published
results in most cases.
Item Type
Article
Associated Schools / Departments
Nottingham University Business School (MY)
Date Deposited
February 19, 2026
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