Preference Guided Iterated Pareto Referent Optimisation for Accessible Route Planning

TL;DR

The paper introduces PG-IPRO, an interactive algorithm for urban route planning that efficiently incorporates user preferences and accessibility needs without computing the entire Pareto front.

Contribution

It presents a novel iterative optimization method that enhances user interaction and computational efficiency in accessible route planning.

Findings

Enables intuitive user feedback during route optimization.

Reduces computational load by avoiding full Pareto front computation.

Improves user experience with shorter waiting times.

Abstract

We propose the Preference Guided Iterated Pareto Referent Optimisation (PG-IPRO) for urban route planning for people with different accessibility requirements and preferences. With this algorithm the user can interact with the system by giving feedback on a route, i.e., the user can say which objective should be further minimized, or conversely can be relaxed. This leads to intuitive user interaction, that is especially effective during early iterations compared to information-gain-based interaction. Furthermore, due to PG-IPRO's iterative nature, the full set of alternative, possibly optimal policies (the Pareto front), is never computed, leading to higher computational efficiency and shorter waiting times for users.