Dr. Reut Noham.
Researcher at the Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University
About Me
I am a faculty member and the head of the Lab for Healthcare and Non-for-Profit Operations at the Department of Industrial Engineering at Tel-Aviv University. I was a post-doctoral fellow at the Department of Industrial Engineering and Management Sciences at Northwestern University and received my Ph.D. degree in Industrial Engineering from Tel-Aviv University in 2019. My research interests include supply chain management and logistics with a focus on humanitarian supply chains, healthcare systems, and non-profit optimization. I employ Analytics and OR tools to model and analyze problems and solution methods to improve the quality of life in an uncertain world. At the Lab for Healthcare and Non-for-Profit Operations, we develop innovative and implementable models for dynamic decision-making in collaboration with policymakers and practitioners from the public sector. I am committed to advancing innovative scientific solutions while providing a platform for engaging policymakers and the public with our cutting-edge research.
Latest Publication
Dual mode scheduling in volunteer management
Escallon-Barrios, Mariana, Reut Noham, Karen Smilowitz. (2023), Socio-Economic Planning Sciences.
Nonprofit organizations have adopted online scheduling platforms that give autonomy to volunteers in the scheduling process. However, this strategy can create imbalances in task coverage, often requiring staff to fill the gaps. The aim of this study is to develop scheduling strategies to create a balanced schedule that effectively combines workforce types (paid staff and volunteers) while keeping volunteers engaged. This is achieved by accounting for volunteers’ responses to changes in scheduling options. We develop an optimization model that recognizes volunteers’ scheduling responses and utilizes these responses to design policies aimed at achieving a balanced coverage across time slots. This involves reducing over-covered and under-covered time slots over the planning horizon. By understanding the preferences of volunteers, organizations can modify their current policies to better match supply with demand keeping their volunteers engaged. We provide an implementable scheduling strategy combining staff assignment and volunteers’ autonomy in scheduling choices. Case study results show an improvement compared to current scheduling policies. Volunteers’ satisfaction increases, resulting in a long-term impact on the organizations and the communities they serve.
Recent projects
Enhancing Humanitarian Supply Chain Resilience through Lateral Transshipments: A Novel Modeling Approach
Reut Noham, Ohad Eisenhandler
Lateral transshipments allow facilities that are at the same echelon in the supply chain to share inventory. They have been extensively explored in the context of commercial supply chains and have been shown to provide an effective way to enhance responsiveness. In this paper, we investigate the potential benefit that can arise from incorporating transshipments in the context of humanitarian supply chains. Specifically, we consider the problem of determining how to pre-position relief supplies in a set of facilities before any disaster occurs, under the assumption the transshipments may be performed at the post-disaster phase. The setting we consider involves a discrete set of disaster scenarios and a budget constraint. We discuss the modelling challenges associated with the unique characteristics of humanitarian operations under uncertainty, and show that "traditional" modeling approaches, such as maximizing expected utility, may lead to solutions that are undesirable from practitioners' perspectives. As an alternative, we propose a modeling approach that has not been applied so far in the literature, to handle the well-known effectiveness-equity trade-off, while also accounting for efficiency. This approach maximizes the humanitarian benefit achieved in each scenario, while simultaneously ensuring that the attention given to each scenario is in line with the probability attributed to it. Through a series of numerical experiments, we compare the outcomes of these modeling approaches; demonstrate how transshipments may affect pre-disaster inventory decisions and make disaster response more effective and equitable; and highlight the characteristics of cases in which transshipments may prove to be especially beneficial
Multi-Session Appointment Scheduling with Heterogeneous Clients
Reut Noham, Karen Smilowitz
Clients seeking paramedical therapies and rehabilitation services generally require frequent appointments over an extended period. Motivated by an early intervention program that provides therapeutic services to infants and toddlers with developmental delays and disabilities, we study scheduling policies that are designed to meet the needs of heterogeneous clients and the operational considerations of the providers. The clients can be heterogeneous in many dimensions: availability and preferences over time, length of service needed, and urgency of need. We aim to better understand how the different ways a provider may prioritize these factors influence scheduling decisions. To do so, the problem of assigning clients to available days and time slots of the service provider is described as a Markov Decision Process. Clients are assigned as requests arrive when only probabilistic knowledge of future clients is known. Given the characteristic of the client and the availability of the provider, our model determines which client requests (specifying day and slot) the service provider should accept in line with a specified prioritization of the provider. We characterize the structural properties of optimal scheduling decisions under idealized conditions. We then use these properties to develop a heuristic for general cases. We evaluate the performance of this heuristic relative to intuitive rule-of-thumb heuristics. Ultimately, we show that dynamic scheduling policies can decrease the number of rejected requests and improve health outcomes while maintaining high utilization of service providers.