3 Presentations

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  01:30 PM - 01:55 PM

  A Stochastic Nurse-to-Patient Assignment Problem with Stochastic Demands and Stochastic Skill Requirements

  • Ngoc Dai Nguyen, presenter, Udem
  • Nadia Lahrichi, Polytechnique Montréal
  • Chunlong Yu, School of Mechanical Engineering, Tongji University, Shanghai, China

  In Home Health Care operations, assigning nurses to patients is a critical task that impacts the service quality and operational costs. Recent studies start to consider the uncertainties in patients’ demand, but seldom take into account the fact that patients' conditions may change and require different services. To this end, we consider the uncertainties in both patients' demand and skill requirements, and propose several policies to minimize the nurse overtime cost and re-assignment penalty. The efficiency of the policies and the impact of the problem characteristic are evaluated through extensive computational experiments.
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  01:55 PM - 02:20 PM

  A Heuristic Algorithm for the Home Health Care Scheduling Problem with a mix of Predefined and Stochastic Visits

  • Clélia Merel, presenter, Polytechnique Montréal
  • Nadia Lahrichi, Polytechnique Montréal
  • Ola Jabali, Politecnico di Milano

  The home health care scheduling problem assigns a set of home care visits over a discrete set of time periods, aiming to minimize the total travel time over all periods, while meeting patients’ availabilities and care provider work time constraints. Inspired by a real case, we consider an agency needing to serve a set of deterministic patients with associated availabilities, known at the beginning of the planning horizon, and an uncertain set of stochastic customers, revealed at the beginning of each period. Stochastic customers are considered urgent and must be served in the period they appear in, which may require rescheduling of deterministic customers. We consider a weighted objective function that minimizes the realized travel costs, as well as the number of rescheduled patient visits in order to reduce patient discomfort. We develop a two-stage heuristic. The first stage generates a partition of the deterministic patients between the periods, while allowing for a good insertion of the stochastic visits, using continuous approximations to estimate the size of the routes. The second stage consists of an online algorithm that modifies the first stage planning to include stochastic patients. We compare the efficiency of our method to a number of standard policies.
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  02:20 PM - 02:45 PM

  Optimizing Home Health Care Services through Integrated Districting and Nurse Allocation under Stochastic Demand

  • Ngoc-Dai Nguyen, presenter, Department of Computer Science and Operations Research, Université de Montréal and CIRRELT, Canada
  • Nadia Lahrichi, Polytechnique Montréal
  • María I. Restrepo, IMT Atlantique
  • Soumen Atta, Center for Information Technologies and Applied Mathematics, School of Engineering and Management, University of Nova Gorica, Slovenia

  This paper presents a comprehensive study of the joint districting and staffing problems in Home Health Care services, taking into account the uncertainty in demand.
  The objective is to optimize the compactness and workload balance measures of both districts and nurses.
  The problem is formulated as a two-stage stochastic program, where the contiguity requirements are explicitly defined for both districts and basic territorial units assigned to nurses. To address the need for stability in districting for several years, the model includes the uncertainty in demand.
  The problem is analyzed in various settings encountered in practice.
  Extensive computational experiments are conducted to investigate the impact of problem characteristics.
  Overall, the study provides insights into optimizing resource allocation in home healthcare services and offers useful methods for decision-makers to improve the efficiency and quality of patient care.