Advance Scheduling with Personalized Learning

Posted: 10 Mar 2020

See all articles by Mohammad Zhalechian

Mohammad Zhalechian

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Esmaeil Keyvanshokooh

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Cong Shi

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Mark P. Van Oyen

University of Michigan at Ann Arbor

Date Written: January 17, 2020

Abstract

Joint online learning and resource allocation is a fundamental problem inherent in many applications. In this problem, an agent must allocate resources while adaptively learning the distributions of unknown parameters under delayed feedback. We introduce a general personalized framework that judiciously synergizes online learning with a broad class of online resource allocation mechanisms with uncertainty in the distributions of both rewards and resource consumption. We prove that our framework has a sub-linear Bayesian regret. As an application of our framework, we develop a contextual learning and optimization algorithm called the Personalized Scheduling while Learning with Delay (PSLD) and evaluate its theoretical performance as well. The PSLD algorithm offers an appointment (server-date) in an online manner to each arriving customer based on the contextual information on the customer and servers, and the limited capacity of the system. It operates under uncertainty in both heterogeneous rewards and service times as well as adversarial arrivals. We demonstrate the practicality and efficacy of our algorithm using real clinical data from a partner health system. Our results show that the proposed online algorithm provides promising results compared to other algorithms and outperforms the pervasive First-Come-First-Served policy by a large margin.

Keywords: advance scheduling, online learning, contextual bandit; online resource allocation; regret analysis; personalized healthcare services

Suggested Citation

Zhalechian, Mohammad and Keyvanshokooh, Esmaeil and Shi, Cong and Van Oyen, Mark P., Advance Scheduling with Personalized Learning (January 17, 2020). Available at SSRN: https://ssrn.com/abstract=3538509

Mohammad Zhalechian (Contact Author)

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
IOE Department
Ann Arbor, MI 48109
United States

Esmaeil Keyvanshokooh

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Cong Shi

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Mark P. Van Oyen

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

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