Piecewise linear value function approximations in nonlinear dynamic scheduling problems with VTOLs

TL;DR

This paper introduces a numerical framework for efficiently scheduling multiple VTOLs by combining a mixed-integer bilevel optimization with piecewise linear value function approximations, enabling optimal trajectory planning.

Contribution

It presents a novel approach that recasts a bilevel optimization problem into a single-level MINLP using piecewise linearization, facilitating efficient numerical solutions for VTOL scheduling.

Findings

The approach is feasible and effective for complex VTOL scheduling problems.

Numerical results demonstrate the method's ability to compute optimal trajectories.

The framework integrates scheduling and trajectory planning into a unified optimization model.

Abstract

Modern vertical take-off and landing vehicles (VTOLs) could significantly affect the future of mobility. The broad range of their application fields encompasses urban air mobility, transportation and logistics as well as reconnaissance and observation missions in a military context. This article presents an efficient numerical framework for dynamic scheduling of multiple VTOLs. It combines a scheduling problem with optimal trajectory planning. The whole setting is formulated as a mixed-integer bilevel optimization problem. At the upper level, VTOLs are scheduled, and their starting times are computed. The solution of the lower level problem involves the computation of a value function and yields optimal trajectories for every aerial vehicle. In order to solve the bilevel problem,it is recast into a single-level one. The resulting mixed-integer nonlinear program (MINLP) is then piecewise linearized and solved numerically by a linear solver based on the Branch-and-Bound algorithm. Numerical results prove the feasibility of the approach proposed in this work.