A distributed approach for robust, scalable, and flexible dynamic ridesharing

This dissertation provides a solution to dynamic ridesharing problem, a NP-hard optimization problem, where a fleet of vehicles move on a road network and ridesharing requests arrive continuously. The goal is to optimally assign vehicles to requests with the objective of minimizing total travel distance of vehicles and satisfying constraints such as vehicles’ capacity and time window for pick-up and drop-off locations. The dominant approach for solving dynamic ridesharing problem is centralized approach that is intractable when size of the problem grows, thus not scalable. To address scalability, a novel agent-based representation of the problem, along with a set of algorithms to solve the problem, is proposed. Besides being scalable, the proposed approach is flexible and, compared to centralized approach, more robust, i.e., vehicle agents can handle changes in the network dynamically (e.g., in case of a vehicle breakdown) without need to re-start the operation, and individual vehicle failure will not affect the process of decision-making, respectively. In the decentralized approach the underlying combinatorial optimization is formulated as a distributed optimization problem and is decomposed into multiple subproblems using spectral graph theory. Each subproblem is formulated as DCOP (Distributed Constraint Optimization Problem) based on a factor graph representation, including a group of cooperative agents that work together to take an optimal (or near-optimal) joint action. Then a min-sum algorithm is used on the factor graph to solve the DCOP. A simulator is implemented to empirically evaluate the proposed approach and benchmark it against two alternative approaches, solutions obtained by ILP (Integer Linear Programming) and a greedy heuristic algorithm. The results show that the decentralized approach scales well with different number of vehicle agents, capacity of vehicle agents, and number of requests and outperforms: (a) the greedy heuristic algorithm in terms of solution quality and (b) the ILP in terms of execution time

Matching mechanisms for two-sided shared mobility systems

Shared mobility systems have gained significant attention in the last few decades due, in large part, to the rise of the service-based sharing economy. In this thesis, we study the matching mechanism design of two-sided shared mobility systems which include two distinct groups of users. Typical examples of such systems include ride-hailing platforms like Uber, ride-pooling platforms like Lyft Line, and community ride-sharing platforms like Zimride. These two-sided shared mobility systems can be modeled as two-sided markets, which need to be designed to efficiently allocate resources from the supply side of the market to the demand side of the market. Given its two-sided nature, the resource allocation problem in a two-sided market is essentially a matching problem. The matching problems in two-sided markets present themselves in decentralized and dynamic environments. In a decentralized environment, participants from both sides possess asymmetric information and strategic behaviors. They may behave strategically to advance their own benefits rather than the system-level performance. Participants may also have their private matching preferences, which they may be reluctant to share due to privacy and ethical concerns. In addition, the dynamic nature of the shared mobility systems brings in contingencies to the matching problems in the forms of, for example, the uncertainty of customer demand and resource availability. In this thesis, we propose matching mechanisms for shared mobility systems. Particularly, we address the challenges derived from the decentralized and dynamic environment of the two-sided shared mobility systems. The thesis is a compilation of four published or submitted journal papers. In these papers, we propose four matching mechanisms tackling various aspects of the matching mechanism design. We first present a price-based iterative double auction for dealing with asymmetric information between the two sides of the market and the strategic behaviors of self-interested agents. For settings where prices are predetermined by the market or cannot be changed frequently due to regulatory reasons, we propose a voting-based matching mechanism design. The mechanism is a distributed implementation of the simulated annealing meta-heuristic, which does not rely on a pricing scheme and preserves user privacy. In addition to decentralized matching mechanisms, we also propose dynamic matching mechanisms. Specifically, we propose a dispatch framework that integrates batched matching with data-driven proactive guidance for a Uber-like ride-hailing system to deal with the uncertainty of riders’ demand. By considering both drivers’ ride acceptance uncertainty and strategic behaviors, we finally propose a pricing mechanism that computes personalized payments for drivers to improve drivers' average acceptance rate in a ride-hailing system

Opérationnaliser les compétences transversales en analyse bibliométrique et en visualisation des réseaux au thème de l’économie collaborative

Une analyse bibliométrique utilisant la visualisation de réseaux pour représenter le thème de l’Économie collaborative (ÉC) au sein de la recherche scientifique a été réalisée dans le cadre de ce mémoire. Pour ce faire, 729 documents ont été recensés sur deux bases de données (Scopus et Web of Science). Ces documents ont été désambiguïsés, nettoyés et standardisés pour être compilés et analysés avec BibExcel et VOSviewer. Différentes statistiques bibliométriques et analyses non évaluatives (cooccurence, cocitation, coauteur) ont pu être exécutées et visualisées afin de mieux comprendre le milieu de l’ÉC. Les résultats de cette recherche sont multiples. D’une part, l’importance des États-Unis est notoire, autant au niveau des auteurs, des organisations que des collaborations. Ensuite, différentes grappes thématiques ont pu être formées selon la variable étudiée. L’importance de la technologie, du tourisme, du développement durable, de l’aspect managérial et enfin de la théorie/conceptualisation de l’ÉC est récurrente. Plusieurs auteurs sont déterminants dans la littérature, mais les plus influents sont Russel Belk et Rachel Botsman. Le livre What’s yours is mine (Botsman et Rogers, 2010) est le document le plus cité, et ce malgré le fait qu’il soit écrit par des auteurs ne provenant pas du milieu académique. Les relations entre les publications étudiées démontrent une cohésion entre les différentes idées et thématiques véhiculées dans le domaine, et ce malgré le fait qu’il existe des problèmes définitionnels et conceptuels à propos de l’ÉC. Enfin, l’évolution chronologique des publications subit une croissance très importante depuis 2016 et témoigne d’un champ de recherche émergent : le développement durable. La somme des résultats analysés donne un nouveau regard sur l’ÉC. Elle permet pour les nouveaux chercheurs de les introduire aux caractéristiques du domaine et sert aux experts à cerner les thématiques, revues et auteurs à considérer lors de leurs propres analyses. La méthodologie et les résultats de cette recherche furent publiés dans le Journal of Cleaner Production (Ertz & Leblanc-Proulx, 2018), le Journal of Markteing Analytics (Ertz & Leblanc-Proulx, 2019a) et le livre Sage Research methods Cases (Ertz & Leblanc-Proulx, 2019b)