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CLUE: Research-in-Progress Meeting

September 22 @ 12:00 pm 1:00 pm EDT

CLUE: Research-in-Progress Meetings are closed events for the CLUE community.

Moderator

Azin Golrizkhatami (University of Toronto—Prof. Matt Roorda)

Agenda

12:05-12:20 Ahana Malhotra  (McMaster University—Prof. Elkafi Hassini)

Abstract: Ride-hailing platform provides an app-based platform to match passengers who wish to take ride with a nearest available driver which act as an independent agent. We provide a ride-hailing model with the service-time restriction and regulated wages of drivers by the regulatory council. Optimal solution using KKT conditions is provided for this model and then numerical analysis is done to gain insights of working of model. Affect of service time and regulated wages is discussed on all the components of ride-hailing platforms (i.e. passenger, drivers, app-based platform) and finally different scenarios for business will be discussed.

  • 12:20-12:35 Artem Solovey  (York University—Prof. Gingerich and Prof. Nourinejad)

Abstract: The efficiency of transportation systems is historically hindered by low vehicle occupancy. There are well-known options to improve this efficiency, such as ride-hailing and ride-sharing services, but these modes are often limited to passenger travel only. In the supply chain industry, there have been recent innovations to combine less-than-truckload (LTL) and crowd-shipping as a method of improving the occupancy and space usage of freight vehicles. The two individual systems for passengers and freight have the potential to be combined as a hybrid ride-sharing system. The combination of passenger and freight and strategies such as Freight on Transit (FOT) works successfully in various transportation modes such as air crafts and trains, yet research utilizing private vehicles in this regard is quite new, and traditional approaches still deal with these deliveries using separate systems. However, recent technology advances and the popularity of emerging tech-based ridesharing platforms provide an emerging opportunity that has not yet been fully examined. This paper proposes a novel model of hybrid ride-sharing currently in development for the York University student community traveling to Keele Campus as an alternative to passenger-only ride-sharing. This paper proposes a model that includes matchmaking and routing for dual delivery of people and packages to a single destination. The Benders Decomposition algorithm is applied to solve the problem due to the inherent complexity. This model can maximize the profits of a ride-share company and increase the utility of all users. In addition, the results from this model can provide broader contributions to social, economic, environmental, and technological sustainability.

Short biographies

Ahana Malhotra has bachelor and master’s in engineering from India and holds an MBA degree from USA. She has total six years of working experience in academia and industry, and is currently pursuing PhD in Management Science at McMaster University under the supervision of Prof. Elkafi Hassini. Her current research areas are ride-hailing-platform and volunteer management. Today she will be discussing the effects of minimum wage regulation and service-time threshold in the ride-hailing platform.

Artem Solovey is a Civil Engineering Master’s student at York University working on the next generation of ridesharing. He is a founder of a ride-share company called YuRide where he applies his research and works with the entrepreneurial space on campus turning ideas into reality at the BEST Lab. He is an avid outdoor person, a professional multitasker, and above all, an opportunist.

Azin Golrizkhatami is a first-year PhD student at the University of Toronto. Her current research focuses on crowd shipping services and the application of Artificial Intelligence (AI) for them under the supervision of Professor Matthew Roorda. She holds a BSc in civil engineering and an MSc in transportation engineering from Sharif University of Technology.

City Logistics for the Urban Economy (CLUE)