Mehrdad Shahabi

Robust Optimization Strategy for the Shortest Path Problem under Uncertain Link Travel Cost Distribution

This article showed how numerical experiments conducted on small to large networks compare the robust optimization-based strategy to the classical deterministic shortest path in terms of the uncertainty. A robust optimization approach for the shortest path problem where travel cost is uncertain and exact information on the distribution function is unavailable is developed. The article showed that under such conditions the robust shortest path problem can be formulated as a binary nonlinear integer program, which can then be reformulated as a mixed integer conic quadratic program. This article presented an outer approximation algorithm as a solution algorithm, which is shown to be highly efficient for this class of programs.

Network Route Choice Model for Battery Electric Vehicle Drivers with Different Risk Attitudes

Research on the range anxiety of battery electric vehicle (BEV) drivers is limited, and research on the route choice of such drivers has been restricted to a fixed range limit modeled as a distance constrained shortest path problem. In this paper, a more general network route choice model based on the range anxiety of BEV drivers is formulated as a nonadditive shortest path problem. More appropriate for BEVs, a tour-based analysis with a continuum of range limits is considered, and an outer approximation algorithm has been used to find the optimal path. Numerical experiments on a small network demonstrate how the routes taken by BEV drivers are influenced by their risk attitudes and uncertainty in the predicted range of the vehicle.

Model for Network Assignment Problem of Capacitated Freight with Disruptions

A modeling framework is proposed for the freight network assignment problem with recourse, network travel time and cost disruptions, and link flow capacity constraints. “Recourse” is defined as the ability of a user to reconsider and adapt his or her routing decisions in response to newly acquired information about network disruption. When real-time tracking and monitoring of network shipments allow companies a routing recourse, network capacity must be simultaneously considered. If a disruption significantly alters network flows, the capacity of alternative or secondary routes may be quickly reached. A new freight mathematical model with a capacitated network and adaptive routing was developed and solved. Results showed that simultaneous consideration of recourse and capacity constraints was superior to benchmark results obtained with nonadaptive deterministic behavior.