arXiv subjects

Richard D. Connors

Publications and source records attributed to Richard D. Connors.

5 recordsLinked to original sources

arXiv2026

Congestion-Aware Charging Coordination for Electric Ride-Hailing Fleets under Stochastic Demand

Charging-station capacity strongly affects the profitability of electric ride-hailing systems. In this study, we develop a dynamic charging scheduling method that anticipates vehicles' energy needs and coordinates their charging operations with real-time energy prices to avoid long waiting time at charging stations and increase the total profit of the system. A sequential mixed integer linear programming model is proposed to devise vehicles' day-ahead charging plans based on their experienced charging waiting times and energy consumption. The developed charging policy is tested on a Manhattan-like study area using synthetic data drawn from NYC yellow taxi data with a fleet size of 100 vehicles given the scenarios of 3000 and 4000 customers/day. The computational results show that our method outperforms different benchmark policies with up to +19.32% profit and +20.03% service rate for 4000 customers relative to the weakest benchmark; relative to the strongest benchmark (OptChg), the corresponding gains are +3.91% profit and +4.60% service rate. Sensitivity analysis is conducted with different system parameters and managerial insights are discussed.

math.OC↗

arXiv2025

Optimal mixed fleet and charging infrastructure planning to electrify demand responsive feeder services with target CO2 emission constraints

Electrifying demand-responsive transport systems need to plan the charging infrastructure carefully, considering the trade-offs of charging efficiency and charging infrastructure costs. Earlier studies assume a fully electrified fleet and overlook the planning issue in the transition period. This study addresses the joint fleet size and charging infrastructure planning for a demand-responsive feeder service under stochastic demand, given a user-defined targeted CO2 emission reduction policy. We propose a bi-level optimization model where the upper-level determines charging station configuration given stochastic demand patterns, whereas the lower-level solves a mixed fleet dial-a-ride routing problem under the CO2 emission and capacitated charging station constraints. An efficient deterministic annealing metaheuristic is proposed to solve the CO2-constrained mixed fleet routing problem. The performance of the algorithm is validated by a series of numerical test instances with up to 500 requests. We apply the model for a real-world case study in Bettembourg, Luxembourg, with different demand and customised CO2 reduction targets. The results show that the proposed method provides a flexible tool for joint charging infrastructure and fleet size planning under different levels of demand and CO2 emission reduction targets.

math.OC↗

arXiv2024

A hybrid metaheuristic to optimize electric first-mile feeder services with charging synchronization constraints and customer rejections

This paper addresses the on-demand meeting-point-based feeder electric bus routing and charging scheduling problem under charging synchronization constraints. The problem considered exhibits the structure of the location routing problem, which is more difficult to solve than many electric vehicle routing problems with capacitated charging stations. We propose to model the problem using a mixed-integer linear programming approach based on a layered graph structure. An efficient hybrid metaheuristic solution algorithm is proposed. A mixture of random and greedy partial charging scheduling strategies is used to find feasible charging schedules under the synchronization constraints. The algorithm is tested on instances with up to 100 customers and 49 bus stops/meeting points. The results show that the proposed algorithm provides near-optimal solutions within less one minute on average compared with the best solutions found by a mixed-integer linear programming solver set with a 4-hour computation time limit. A case study on a larger sized case with 1000 customers and 111 meeting points shows the proposed method is applicable to real-world situations.

math.OC↗

arXiv2024

Optimized electrified meeting-point-based feeder bus services with capacitated charging stations and partial recharges

Meeting-point-based feeder services using EVs have good potential to achieve an efficient and clean on-demand mobility service. However, customer-to-meeting-point, vehicle routing, and charging scheduling need to be jointly optimized to achieve the best system performance. To this aim, we assess the effect of different system parameters and configure them based on our previously developed hybrid metaheuristic algorithm. A set of test instances based on morning peak hour commuting scenarios between the cities of Arlon and Luxembourg are used to evaluate the impact of the set parameters on the optimal solutions. The experimental results suggest that higher meeting point availability can achieve better system performance. By jointly configuring different system parameters, the overall system performance can be significantly improved (-10.8% total kilometers traveled by vehicles compared to the benchmark) to serve all requests. Our experimental results show that the meeting-point-based system can reduce up to 70.2% the fleet size, 6.4% the in-vehicle travel time and 49.4% the kilometers traveled when compared to a traditional door-to-door dial-a-ride system.

math.OC↗

arXiv2023

A Multi-Modal Network Equilibrium Model with Interacting Mobility Service Providers'Strategies

A Mathematical Program with Equilibrium Constraints (MPEC) is formulated to capture the relationships between multiple Mobility Service Providers (MSPs) and the users of a multi-modal transport network. The network supply structure is defined through a novel supernetwork approach where users' daily trip chains are represented to model the mobility services used to reach each destination. At the upper level, a profit maximization formulation is introduced to describe each MSPs' behaviour. At the lower level, users within a class choose minimum cost routes, according to Wardrop's first equilibrium principle. To consider the interactions between modes, non-separable costs between supernetwork links are defined, and users' equilibrium conditions are formulated as a Variational Inequality (VI). To solve the MPEC, an iterative solution algorithm based on a Modified Projection Method is proposed. Numerical examples are presented to illustrate properties of the model, and to examine scenarios showcasing cooperation or competition strategies between MSPs.

cs.GT↗