Publications

S Shocks, seasonality, and disaggregation: Modelling food security through the integration of agricultural, transportation, and economic systems

Leave a Comment / Health, Peer-reviewed Journal Articles, Publications, Transportation /

Bakker, C., Zaitchik, B. F., Siddiqui, S., Hobbs, B. F., Broaddus, E., Neff, R. A., Haskett, J., Parker, C. L., (2018)

Shocks, seasonality, and disaggregation: Modelling food security through the integration of agricultural, transportation, and economic systems

Agricultural Systems, 164: 165-184

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S Sensitivity and covariance in stochastic complementarity problems with an application to the North American natural gas markets

Leave a Comment / Energy, Peer-reviewed Journal Articles, Publications /

Sankaranarayanan, S., Feijoo, F., & Siddiqui, S., ( 2018 )

Sensitivity and covariance in stochastic complementarity problems with an application to the North American natural gas markets

European Journal of Operational Research, 268(1): 25-36

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G Policy implications of incorporating distance constrained electric vehicles into the traffic network design problem

Leave a Comment / Peer-reviewed Journal Articles, Publications, Transportation /

Tao Wen, Lauren Gardner, Vinayak Dixit, S. Travis Waller, Chen Cai, Fang Chen (2018)

Policy implications of incorporating distance
constrained electric vehicles into the traffic
network design problem

Transportation Letters, 10:3

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S An exact solution method for binary equilibrium problems with compensation and the power market uplift problem

Leave a Comment / Energy, Peer-reviewed Journal Articles, Publications /

Huppmann, D., Siddiqui, S., ( 2018 )

An exact solution method for binary equilibrium problems with compensation and the power market uplift problem

European Journal of Operational Research, 266(2): 622-638

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G A Strategic User Equilibrium for Independently Distributed Origin-Destination Demands

Leave a Comment / Peer-reviewed Journal Articles, Publications, Transportation /

Tao Wen, Lauren Gardner, Vinayak Dixit, S. Travis Waller, Chen Cai, Fang Chen (2018)

A Strategic User Equilibrium for Independently
Distributed Origin-Destination Demands

Computer-Aided Civil and Infrastructure Engineering, 33

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G Two Methods to Calibrate the Total Travel Demand and Variability for a Regional Traffic Network

Leave a Comment / Peer-reviewed Journal Articles, Publications, Transportation /

Tao Wen, Lauren Gardner, Vinayak Dixit, S. Travis Waller, Chen Cai, Fang Chen (2018)

Two Methods to Calibrate the Total Travel Demand
and Variability for a Regional Traffic Network

Computer-Aided Civil and Infrastructure Engineering, 33

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G Two Methods to Calibrate the Total Travel Demand and Variability for a Regional Traffic Network Read More »

Many outpatient facilities with expensive resources, such as infusion and imaging centers, experience surge in their patient arrival at times and are under-utilization at other times. This pattern results in patient safety concerns, patient and staff dissatisfaction, and limitation in growth, among others. Scheduling practices is found to be one of the main contributors to this problem.

We developed a real-time scheduling framework to address the problem, specifically for infusion clinics. The algorithm assumes no knowledge of future appointments and does not change past appointments. Operational constraints are taken into account, and the algorithm can offer multiple choices to patients.

We generalize this framework to a new scheduling model and analyze its performance through competitive ratio. The resource utilization of the real-time algorithm is compared with an optimal algorithm, which knows the entire future. It can be proved that the competitive ratio of the scheduling algorithm is between 3/2 and 5/3 of an optimal algorithm.

This work was performed with the MIT/MGH Collaboration.

In many healthcare services, care is provided continuously, however, the care providers, e.g., doctors and nurses, work in shifts that are discrete. Hence, hand-offs between care providers is inevitable. Hand-offs are generally thought to effect patient care, although it is often hard to quantify the effects due to reverse causal effects between patients’ duration of stay and the number of hand-off events. We use a natural randomized control experiment, induced by physicians’ schedules, in teaching general medicine teams. We employ statistical tools to show that between the two randomly assigned groups of patients, a subset who experiences hand-off experience a different length of stay compared to the other group.

This work was performed with the MIT/MGH Collaboration.

Primary care is an important piece in the healthcare system that affects the downstream medical care of patients heavily. There are specific challenges in primary care as healthcare shifts from fee-for-service to population health management and medical home, focuses on cost savings and integrates quality measures. We consider the primary care unit at a large academic center that is facing similar challenges. In this work we focus on the imbalance in workload, which is a growing regulatory burden and directly concerns any staff in primary care. It can result in missed opportunities to deliver better patient care or providing a good work-environment for the physicians and the staff. We consider the primary care unit at the large academic center and focus on their challenge in balancing staff time with quality of care through a redesign of their system. We employ optimization models to reschedule providers’ sessions to improve the patient flow, and through that, a more balanced work-level for the support staff. 

This work was performed with the MIT/MGH Collaboration.

Perioperative services are one of the vital components of hospitals and any disruption in their operations can leave a downstream effect in the rest of the hospital. A large body of evidence links inefficiencies in perioperative throughput with adverse clinical outcomes. A regular delay in the operating room (OR), may lead to overcrowding in post-surgical units, and consequently, more overnight patients in the hospital. Conversely, an underutilization of OR is not only a waste of an expensive and high-demand resource, but it also means that other services who have a demand are not able to utilize OR. This mismatch in demand and utilization may, in turn, lead to hold-ups in the OR and cause further downstream utilization. We investigate the utilization of operating rooms by each service. The null hypothesis of this work is that the predicted utilization of the OR, i.e., the current block schedule, matches completely with the actual utilization of the service. We test this hypothesis for different utilization definitions, including physical and operational utilization and reject the null hypothesis. We further analyze why a mismatch may exist and how to optimize the schedule to improve patient flow in the hospital.

In radiation therapy with continuous dose delivery for Gamma Knife® Perfexion™, the dose is delivered while the radiation machine is in movement, as oppose to the conventional step-and-shoot approach which requires the unit to stop before any radiation is delivered. Continuous delivery can increase dose homogeneity and decrease treatment time. To design inverse plans, we first find a path inside the tumor volume, along which the radiation is delivered, and then find the beam durations and shapes using a mixed-integer programming optimization (MIP) model. The MIP model considers various machine-constraints as well as clinical guidelines and constraints.

Radiation therapy is frequently used in diagnosing patients with cancer. Currently, the planning of such treatments is typically done manually which is time-consuming and prone to human error. The new advancements in computational powers and treating units now allow for designing treatment plans automatically.

To design a high-quality treatment, we select the beams sizes, positions, and shapes using optimization models and approximation algorithms. The optimization models are designed to deliver an appropriate amount of dose to the tumor volume while simultaneously avoiding sensitive healthy tissues. In this project, we work on finding the best beam positions for the radiation focal points for Gamma Knife® Perfexion™, using quadratic programming and algorithms such as grassfire and sphere-packing.