Optimization of bus routes and stops

RODRIGUEZ D.A.; OTEIZA P.P.; BRIGNOLE N. B.

Bologna

Conferencia; EURO/ALIO International Conference 2018 on Applied Combinatorial Optimization; 2018

International Federation of Operational Research Societies (IFORS)

Urban-transport management is nowadays a challenging topic of great significance [1]. Therefore, it is important to develop an efficient optimization method for this purpose. The proposed algorithm is a hyper-heuristics that can choose and apply the most convenient metaheuristics for the different stages of the search process. The strategy consists in adequately guiding the execution of the following metaheuristics: a Genetic Algorithm, Simulated Annealing, and an Ant Colony Optimization. Moreover, parallel programming was implemented to reduce computational times. The first algorithmic version [2] was significantly improved and the number of evaluations related to the ensuing solutions was successfully minimized. Larger instances were tested (300 stops in 30 zones) and computational times decreased in 15%. This algorithmic development is part of an integral Project [3] that aims at the creation of computational tools for the design of Bahía Blanca city with a future perspective of efficient organization.[1] Prodhon, C., and C. Prins, A survey of recent research on location-routing problems, European Journal of Operational Research 238 (2014), 1-17.[2] Rodriguez D. A., P. P. Oteiza, and N. B. Brignole, Hiperheur´ıstica para el Planeamiento del Transporte Pu´blico, CICCSI 2017, Mendoza, Argentina (2017).[3] Brignole N. B. and V. N. Viego, ?Proyecto CIC: PIT-AP-BA?, Resoluci´on 428-9/16, Argentina (2017).