6 Presentations

• 
  10:30 AM - 10:55 AM

  Peel Pack Planning Using Clustering and Decomposition Approach

  • Yixuan Wang, presenter,

  In order to improve the operational efficiency in the Operating Room, hospitals customize surgical trays for each surgical procedure. Since, surgical procedures involve a variety of patients and surgeons, the usage of surgical instruments (in terms of quantity) differs from case to case. This poses a significant challenge as the variability in instrument usage makes it difficult to determine the optimal quantity for each instrument for each procedure. In this study, we address the issue of excessive waste in surgical trays by proposing the implementation of custom peel packs. These peel packs could be used (in place of a new surgical tray) if the surgical tray ran out of the instruments. Our objective is to reduce waste by designing custom peel packs associated with multiple surgical procedures while ensuring that all the necessary instruments are available during the procedure without opening a new main tray. We present one decomposition approach to finding the exact solution and a simplified fast approach based on clustering and mathematical programming to find the near-optimal solution in a fractional time compared to the exact approach. Numerical experiments demonstrate the performance of the presented approaches. The findings indicate that the proposed K-means-based clustering method is very effective in configuring peel packs.
• 
  10:55 AM - 11:20 AM

  Compact Formulations for the Robust Vehicle Routing Problem with Time Windows under Demand and Travel Time Uncertainty

  • Rafael Ajudarte de Campos, presenter, Department of Operations and Decision Systems, Université Laval
  • Pedro Munari, Department of Production Engineering, Federal University of São Carlos, Brazil
  • Leandro C. Coelho, Université Laval

  We provide new compact formulations for the robust vehicle routing problem with time windows (RVRPTW) under cardinality- and knapsack-constrained demand and travel time uncertainty. Particularly, we propose the first compact model that addresses the RVRPTW under travel time uncertainty considering the knapsack uncertainty set. Our models use different types of constraints to control time propagation based on the well-known Miller-Tucker-Zemlin and single commodity flow constraints. The latter has not been explored even for the deterministic variant of the problem, so we first state them explicitly. We also design tailored branch-and-cut algorithms based on the proposed formulations, which rely on a dynamic programming algorithm to verify if a solution is robust feasible with respect to demand and time, and use specific as well as standard separation methods found in the literature. We present detailed computational results on RVRPTW instances, compare the performance of our models and algorithms, and evaluate the impact and advantages of implementing each studied uncertainty set.
• 
  11:20 AM - 11:45 AM

  A Two-Echelon Location Routing Problem for last-mile delivery

  • Fernando R. Senna, presenter, Federal University of São Carlos and CIRRELT
  • Reinaldo Morabito, Federal University of São Carlos
  • Pedro Munari, Federal University of São Carlos
  • Leandro C. Coelho, Université Laval

  The increasing complexity of last-mile delivery systems creates new challenges and opportunities for practice and research. In this work, we study a two-echelon location routing problem for last-mile delivery with time windows considering a scheme in which vehicles perform routes over some customers while the remaining ones are visited by carriers on foot (or by bike). By effectively creating clusters, the parking locations of the vehicles serve as depots for the second echelon routes that are executed by deliverymen. They may serve customers in parallel, reducing the overall service time and the number of vehicles needed. This problem reflects applications in congested urban areas where the difficulty of finding parking locations and the proximity of customers make it interesting to include more than one deliveryman per vehicle. The problem is an extension of the Vehicle Routing Problem with Time Windows and Multiple Deliverymen, in which decisions on customer clustering and deliverymen routes are not included. We present a formulation for the problem, propose novel sets of valid inequalities for this formulation, and elaborate on exact solution methods. We discuss the cost structure of different instances and assess the performance of the proposed approaches using new and existing instances.
• 
  11:45 AM - 12:10 PM

  Optimal Use of Home Hemodialysis Using Competitive Incentive Plans

  • Maryam Afzalabadi, presenter, Lazaridis School of Business and Economics, Wilfrid Laurier University
  • Mojtaba Araghi, Lazaridis School of Business and Economics, Wilfrid Laurier University
  • Salar Ghamat, Lazaridis School of Business and Economics, Wilfrid Laurier University

  An increasing number of patients with end-stage renal disease receive long-term dialysis every year. Although available evidence suggests that home-based hemodialysis (HHD) may achieve similar clinical outcomes to in-center hemodialysis (ICHD) and are less resource intensive, this treatment modality has been underutilized with dialysis facilities. To increase the utilization rate of HHD, we formulate a target-based incentive model utilizing a comparative approach in the form of exogenous achievement benchmarks alongside the providers’ own improvement. The existing literature on incentive payment models in healthcare has been primarily focused on performance-based and target-based incentive models separately. Furthermore, we propose a novel “competitive” incentive plan in which, instead of exogenous achievement benchmarks, the rank of the providers is the criteria for qualifying for the achievement rewards.

  Our paper is the first in the performance-based payment literature to analytically study incentive models tied to individual performance (improvement) and competition (achievement) simultaneously.

  This approach can be considered a significant development in incentive payment model literature since it can incentivize all the participants to obtain a reward regardless of their initial performance. We obtain the equilibrium solution for target-based and competitive incentive models and analyze the behavior of system equilibria in different environmental and individual settings.
• 
  12:10 PM - 12:35 PM

  Guiding Physicians with Time-dependent Patient Selection Policies

  • Mahdi Shakeri, presenter,
  • Marco Bijvank, University of Calgary

  Physicians in emergency departments (EDs) have their own discretion to select the next patient to be seen. Since they operate under an increased workload, such personalized decisions may lead to practices that are less than optimal from a resource utilization perspective and can negatively impact operational and clinical outcomes. In this work, we derive patient selection strategies to guide ED physicians. This is a complex decision and requires the consideration of several factors such as patients’ severity scores, wait times, and the presence of returning patients. In particular, we present a time-dependent policy where the time remaining in a physician’s shift plays an important role. In particular, any patients who are still under the care of the physician at the end of the shift must be transferred to another physician (i.e., patient hand-offs). This is a practice known to compromise the quality of patient care. We formulate an optimal control problem by considering a cost function that captures patient wait times, their acuity, and patient hand-offs. Numerical experiments demonstrate that our proposed time-dependent patient selection policy significantly reduces patient hand-offs compared to traditional time-independent policies while maintaining comparable waiting times and length-of-stay durations.
• 
  12:35 PM - 01:00 PM

  Aerial Fleet Planning Using Simulation Models to Improve Interhospital Transport

  • Joëlle Cormier, presenter, HEC Montréal
  • Valérie Bélanger, CIRRELT, HEC Montréal
  • Marie-Eve Rancourt, HEC Montréal

  This project focuses on strategic decisions, which include the composition of the aircraft fleet, the number of aircraft and the location of the hangars. Real data input and simulation modeling were used to improve the fleet of fixed-wing aircraft in the Canadian province of Québec. This study made it possible to develop a methodology to assess the various trade-offs at the strategic level.

  Discrete-event simulation is a tool adapted to this problem since it is obviously not possible to carry out tests with real aircraft. Simulation also incorporates the variability present in this type of transfer, such as meteorological events, and mechanical break. It also sheds light on the key trade-offs in the strategic and operational functioning of an aeromedical evacuation service, such as aircraft speed, capacity and accessibility.

  The close collaboration with the Ministry of Health and Social Services of Quebec allowed to build the model on real data and to offer recommendations specific to the territory and demand for the Canadian province of Quebec. The methodology could be used for different regions around the world or for other types of aerial evacuations.