Karmel S. Shehadeh

Assistant Professor

Lehigh University

United States

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Karmel S. Shehadeh is an Assistant Professor at Lehigh University in the United States. Her research primarily focuses on stochastic optimization, with recent articles exploring topics such as elective surgery planning under uncertainty, multi-resource allocation, and the integration of data-driven approaches in service staffing. Shehadeh's work also addresses equity measures in resource allocation and transportation disparities, contributing valuable insights to the field of operational research.

Articles (16)

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2025

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2025

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2023

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2023

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2023

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2023

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2022

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2022

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2022

Collaborators (3)

Emily Tucker

Assistant Professor

Clemson University

UNITED STATES

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Frank E. Curtis

Professor

Lehigh University

UNITED STATES

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Lifang He

Assistant Professor

Lehigh University

UNITED STATES

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Karmel S. Shehadeh

Research Interests

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Articles (16)

Operating room-to-downstream elective surgery planning under uncertainty

A Unified Framework for Analyzing and Optimizing a Class of Convex Fairness Measures

On the Tradeoff Between Distributional Belief and Ambiguity: Conservatism, Finite-Sample Guarantees, and Asymptotic Properties

Stochastic Optimization Approaches for an Operating Room and Anesthesiologist Scheduling Problem

Multi-resource allocation and care sequence assignment in patient management: a stochastic programming approach

Stochastic programming models for a fleet sizing and appointment scheduling problem with random service and travel times

Development and Application of a Comprehensive Measure of Access to Health Services to Examine COVID-19 Health Disparities

Data-driven integrated home service staffing and capacity planning: Stochastic optimization approaches

Reducing disparities in transportation distance in a stochastic facility location problem

Stochastic optimization models for a home service routing and appointment scheduling problem with random travel and service times

Routing and resource allocation in non-profit settings with equity and efficiency measures under demand uncertainty

An inexact column-and-constraint generation method to solve two-stage robust optimization problems

Distributionally Robust Optimization Approaches for a Stochastic Mobile Facility Fleet Sizing, Routing, and Scheduling Problem

Stochastic optimization models for location and inventory prepositioning of disaster relief supplies

Data-driven distributionally robust surgery planning in flexible operating rooms over a Wasserstein ambiguity

Stochastic optimization approaches for elective surgery scheduling with downstream capacity constraints: Models, challenges, and opportunities

Collaborators (3)

Emily Tucker

Frank E. Curtis

Lifang He

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