Multi-objective design of time-constrained bike routes using bio-inspired meta-heuristics

This paper focuses on the design and implementation of a bike route optimization approach based on multi-objective bio-inspired heuristic solvers. The objective of this approach is to produce a set of Pareto-optimal bike routes that balance the trade-off between the length of the route and its safety level, the latter blending together the slope of the different street segments encompassing the route and their average road velocity. Additionally, an upper and lower restriction is imposed on the time taken to traverse the route, so that the overall system can be utilized for planning bike rides during free leisure time gaps. Instead of designing a discrete route encoding strategy suitable for heuristic operators, this work leverages a proxy software – Open Trip Planner, OTP – capable of computing routes based on three user-level preference factors (i.e. safety, inclination and duration), which eases the adoption of off-the-shelf multi-objective solvers. The system has been assessed in a realistic simulation environments over the city of Bilbao (Spain) using multi-objective bio-inspired approaches. The obtained results are promising, with route sets trading differently distance for safety of utmost utility for bike users to exploit fully their leisure time.