3 Presentations

• 
  10:30 AM - 10:55 AM

  A Time-Discretized Mathematical Model and Heuristic for Breast Cancer Radiotherapy

  • Scholar Sun, presenter, University of Waterloo

  Intensity modulated radiation therapy (IMRT) is a cancer treatment method whereby a high-energy beam is emitted by a linear accelerator (LINAC) to irradiate cancerous tissue. Sliding window IMRT is a technique in which the beam is modulated by a set of tungsten leaves that move unidirectionally across the beam field to produce complex delivery patterns. Planning for this treatment involves specifying a sequence of leaf arrangements and the corresponding time the LINAC takes on this arrangement. Due to the exponentially large number of possible arrangements, this type of treatment can be difficult to plan.

  In this paper, we formulate a mixed integer nonlinear program to optimize the delivery of a sliding-window IMRT procedure wherein the prescribed dosage to the tumors are met and the dose to healthy tissues are minimized. Given the complex nature of the nonlinear MIP model, we propose a heuristic that provides a high-quality feasible solution which can be used as a benchmark for clinical plans. The viability of this model is then demonstrated using patient data. The solutions generated by the model can be directly implemented in clinical treatment planning software to assist planners in improving the quality of plans for cancer patients.
• 
  10:55 AM - 11:20 AM

  Optimizing Product Allocation for Grocery E-Commerce Fulfillment

  • Jenya Sourgaeva, presenter, Simon Fraser University
  • Angelika Nowlan, Simon Fraser University
  • Sanjay Alwani, Simon Fraser University
  • Weiyi Liu, Simon Fraser University

  With the increasing demand for e-commerce services, stores seek to reduce the labour hours required to fulfill online orders. One solution is utilizing more accessible storage types, such as an automated storage system, to reduce trips to the store front. However, this system is restricted in capacity and item compatibility. Therefore, stores must decide how to allocate products optimally across multiple storage locations. This paper provides a model that optimizes the use of automated storage in conjunction with alternative storage options, such that labour time to fulfill online orders is minimized. We model this as a multiple homogeneous binary knapsack problem. Our objective function takes picking–rates and customer product preferences into consideration, subject to a variety of constraints. Our model improves the current labour time by 4% and increases product count in automation by 19%. We provide suggestions for how additional data could provide a solution more aligned with business rules. A sensitivity analysis reveals our solution remains optimal in response to perturbations up to 3.5 standard deviations of the objective function coefficient value. Related literature suggests this type of modeling has applications in staff scheduling, warehouse product sorting, and risk management.
• 
  11:20 AM - 11:45 AM

  A simulation-optimization problem for the VCH's IPN program

  • Jesse Stuparyk, presenter, Simon Fraser University
  • Kyle Tadeo, Simon Fraser University
  • Park Jake, Simon Fraser University
  • Terry Jeong, Simon Fraser University

  This project looks at maximizing accessibility of the Indigenous Patient Navigator (IPN) program for Lions Gate Hospital and Vancouver General Hospital in Vancouver, Canada. The IPN program provides Indigenous self-identifying patients assistance in accessing primary care and community-based health care services. The IPN is responsible for ensuring that patient care occurs in a culturally safe and respectful manner, offering traditional culturally safe resources that complement current healthcare regimes, mitigating potential complaints by acting as a conduit between client and care team through presence, communication, approach, and understanding. The IPN program is growing and expected to increase in demand for the foreseeable future. In collaboration with Vancouver Coastal Health, this paper implements a queuing model using the AnyLogic software program to describe the IPN workflow and patient flow in the hospitals as a simulation optimization problem. We have data based on the hospital's IPN patient tracking sheet, and professional staff opinion to estimate the parameters needed for the queuing model. The input for the simulation optimization model uses a discrete large feasible set and is solved through a multi-objective function using an approximated gradient method to recommend IPN staffing requirements over a given week, and the IPNs' typical workflow. Data and results indicate that extra staffing should be considered anywhere from Sunday to Thursday.