Engineering (Faculty of)

Permanent URI for this communityhttps://uwspace.uwaterloo.ca/handle/10012/9900

Welcome to the Faculty of Engineering community.

This community, its sub-communities, and collections are organized using the University of Waterloo's Faculties and Academics structure. In this structure:

Communities are Faculties or Affiliated Institutions
Sub-communities are Departments or Research Centres
Collections are the arrangement of research types produced by a Department or Research Centre

New sub-communities and collections following this structure will be created UPON REQUEST.

Browse

Now showing 1 - 3 of 3

Mechanisms Driving Service Duration: A Large-Scale Empirical Analysis
(University of Waterloo, 2021-09-28) Eshraghi, Seyyed Mohammad Hossein; Abouee-Mehrizi, Hossein
Using large-scale MRI services data, a multi-type multi-priority scheduling system, we measure service duration and show that a number of covariates, including the shift during which the procedure is performed, patients' priority, case mix workload of the proceeding patients and batching of similar procedures affect service duration. We find that the effects of various mechanisms on service duration may depend on the hospital type (teaching or community hospitals) and customer type (high priority versus low priority patient). For instance, adjusting for other factors, we find that MRI scan duration for emergent patients during the night shifts is significantly longer than the day shifts (around 4%) and the decrease is even higher in teaching hospital settings (around 8%), but low priority patients undergo shorter procedure duration during night shifts. We also show that the inverted-U-shaped relationship observed between the service duration and workload in the literature is also evident in the MRI services. We also find that sequencing consecutive procedures of similar body types is a significant mechanism that reduces patients' MRI scan time. As a result, adding an extra job of a similar scan type reduces the service time by 4%. We find that the effects of workload and sequencing are both endogenous, thus the OLS estimator might fail to determine the true effects. Thereby, we constructed a simultaneous equations model and used a three-stage least square (3SLS) estimator to correct the endogeneity and simultaneity biases of workload and sequencing factors, respectively.
Multi-Class Advance Patient Scheduling
(University of Waterloo, 2021-09-29) Shirani Faradonbeh, Mohamad Sadegh; Abouee-Mehrizi, Hossein
The problem of advance scheduling of service appointments for patients arriving to a healthcare facility received a lot of attentions in the literature of operations management. Broadly speaking, the main goal is on the efficient assignment of patients entering the system to the next operating days, advance in time and in a dynamic manner. In particular, the problem of multi-class advance patient scheduling, that aims to incorporate differences in the priority levels of patient classes, is of interest in many situations. In this setting, one needs to address important challenges to efficiently utilize the limited and costly resources of the underlying healthcare facilities. Furthermore, a reliable scheduling policy needs to reserve sufficient capacity for high-priority patients, in order to avoid long waiting-times for urgent cases in the future. Accordingly, at every time instant, the policy needs to consider all outstanding appointments, as well as uncertainties in the future demand. This work presents the first theoretically tractable framework for design and analysis of efficient advance scheduling policies in a multi-class setting. First, we provide a realistic formulation of the problem that reflects both the transient as well as the long-term behavior of scheduling policies. Then, we study optimal policies that efficiently schedule patients of different classes and characterize the resulting coarse-grained fluid dynamics, as well as the finer dynamics of diffusion approximation. In fact, the former yields to a simple policy that schedules all patients on the day of their arrival, and also sets the stage for the analysis of the latter stochastic dynamical model. Then, we proceed towards considering diffusion processes based on which the study of scheduling policies becomes a Brownian control problem. Finally, by leveraging a dynamic programming approach, we characterize the optimal policy and validate it through numerical implementations.
Perishable Inventory Routing Problem under Uncertainty
(University of Waterloo, 2023-08-24) Khalili, Ghazaleh; Abouee-Mehrizi, Hossein; Ghadimi, Saeed
In an Inventory Routing Problem (IRP), a decision-maker decides the number of units delivered to each retailer and determines delivery routes, which becomes increasingly challenging as the network expands. Incorporating uncertainty and perishability into the IRP gives rise to a more complex problem known as the stochastic Perishable Inventory Routing Problem (PIRP). Traditional approaches, such as dynamic programming, often struggle to efficiently solve this problem. This is due to the curse of dimensionality, which grows exponentially with the number of retailers and the product's shelf life. In this work, we decompose the PIRP into a Perishable Inventory Problem (PIP) and a Vehicle Routing Problem (VRP) and address them sequentially in two distinct phases. By successfully determining the replenishment quantities first, we then solve the VRP using state-of-the-art algorithms. Consequently, our primary focus lies in identifying the optimal replenishment quantities for perishable products. To address the complexities of this problem, we propose a Direct Lookahead Approximation (DLA) policy designed for sequential decision-making problems under uncertainty. Specifically, we employ a two-stage approximation method that considers a limited number of sample paths while still achieving promising results. The problem is formulated as a mixed-integer programming (MIP) model with the objective of minimizing holding, shortage, wastage, and replenishment costs. In this context, a fixed cost is employed as an approximation for the routing costs of the second phase. To enhance the implementation of the DLA policy, we conduct a comprehensive analysis and recommend techniques such as incorporating linear cuts into the MIP model. To evaluate the effectiveness of the policy, we examine a blood supply chain focusing on perishable platelet units. Through extensive experiments, we demonstrate that the proposed policy can significantly outperform several known algorithms in the literature.

Browse

Browsing Engineering (Faculty of) by Author "Abouee-Mehrizi, Hossein"