EURO Working Group on Locational Analysis meeting plenary

I gave a plenary talk at the EURO Working Group for Locational Analysis (EWGLA) XXV Conference entitled “On designing public sector systems.” I am grateful to Prof. Dr. Lieselot Vanhaverbeke, organizer of the 2019 EURO Working Group on Locational Analysis meeting and professor at Vrije Universiteit Brussel (VUB) for inviting me. Her hospitality and the hospitality of the entire conference organizing committee was amazing. They even gave me a box of very nice locally made gourmet speculoos cookies, which I greatly appreciate.

My slides are below.

The references from my presentation capture almost two decades of research. The papers can be found in the Research section of my blog and are listed at the bottom of this blog post.

 

I captured much of my visit on twitter. Here are some highlights:

References:

Aviation security

1.Jacobson, S. H., J. E. Virta, L. A. McLay, J. E. Kobza, 2005.  Integer Program Models for the Deployment of Airport Baggage Screening Security Devices, Optimization and Engineering 6(3) 339 – 359.

2.Jacobson, S. H., L. A. McLay, J. E. Kobza, J. M. Bowman, 2005. Modeling and Analyzing Multiple Station Baggage Screening Security System Performance, Naval Research Logistics 52(1), 30 – 45.

3.McLay, L. A., S. H. Jacobson, and J. E. Kobza, 2006. A Multilevel Passenger Prescreening Problem for Aviation Security, Naval Research Logistics 53 (3), 183 – 197.

4.Lee, A.J., L.A. McLay, and S.H. Jacobson, 2009. Designing Aviation Security Passenger Screening Systems using Nonlinear Control.  SIAM Journal on Control and Optimization 48(4), 2085 – 2105.

5.McLay, L. A., S. H. Jacobson, and A. G. Nikolaev, 2009.  A Sequential Stochastic Passenger Screening Problem for Aviation Security, IIE Transactions 41(6), 575 – 591.

6.McLay, L.A., S.H. Jacobson, A.J. Lee, 2010.  Risk-Based Policies for Aviation Security Checkpoint Screening.  Transportation Science 44(3), 333-349.

Infrastructure Protection

1.  Albert McLay, L., 2015. Discrete optimization models for homeland security and emergency management, TutORial at the 2015 INFORMS Annual Meeting, November 1-4, 2015, Philadelphia, PA.

2.Zheng, K., Albert, L., Luedtke, J.R., Towle, E. 2019. A budgeted maximum multiple coverage model for cybersecurity planning and management, To appear in IISE Transactions. DOI: 10.1080/24725854.2019.1584832

3.Zheng, K., and Albert, L.A. 2019. Interdiction models for delaying adversarial attacks against critical information technology infrastructure. To appear in Naval Research Logistics.

Emergency Medical Services

1.McLay, L.A., 2009.  A Maximum Expected Covering Location Model with Two Types of Servers, IIE Transactions 41(8), 730 – 741.

2.McLay, L.A., 2010. Emergency Medical Service Systems that Improve Patient Survivability. Encyclopedia of Operations Research in the area of “Applications with Societal Impact,” eds. J.J. Cochran, L. A. Cox, Jr., P. Keshinocak, J.C. Smith. John Wiley & Sons, Inc., Hoboken, NJ (published online: DOI: 10.1002/9780470400531.eorms0296).

3.McLay, L.A. and M.E. Mayorga, 2010. Evaluating Emergency Medical Service Performance Measures.  Health Care Management Science 13(2), 124 – 136.

4.McLay, L.A., Mayorga, M.E., 2011.  Evaluating the Impact of Performance Goals on Dispatching Decisions in Emergency Medical Service. IIE Transactions on Healthcare Service Engineering 1, 185 – 196

5.Ansari, S., McLay, L.A., Mayorga, M.E., 2015. A maximum expected covering problem for locating and dispatching servers. To appear in Transportation Science.

6.McLay, L.A., Moore, H. 2012. Hanover County Improves Its Response to Emergency Medical 911 Calls. Interfaces 42(4), 380-394.

7.Ansari, S., McLay, L.A., Mayorga, M.E., 2015. A Maximum Expected Covering Problem for District Design, Transportation Science 51(1), 376 – 390.

8.Grannan, B.C., Bastian, N., McLay, L.A. 2015. A Maximum Expected Covering Problem for Locating and Dispatching Two Classes of Military Medical Evacuation Air Assets. Operations Research Letters 9, 1511-1531.

9.Yoon, S. and Albert, L.A. 2018. Dynamic Resource Assignment for Emergency Response with Multiple Types of Vehicles, Under review at Operations Research, October 2018.

10.Yoon, S., and Albert, L.A. 2019. A dynamic ambulance routing model with multiple response. Under review at Transportation Research Part E: Logistics at Transportation Science.

 

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2019 INFORMS Government and Analytics Summit: a recap

I again chaired the INFORMS Government & Analytics Summit in Washington, D.C. on May 20, 2019. The Summit brought together INFORMS experts with policymakers from Capitol Hill, federal agencies, and other policy stakeholders to showcase impactful ways in which operations research tools are being used to save lives, save money and solve problems in the public and private sectors. Pictures from the Summit are below.

Secretary John McHugh gave the keynote talk. INFORMS President Ramayya Krishnan and INFORMS Executive Director Melissa Moore also gave some remarks.

I chaired the panel with panelists Bala Ganesh (UPS), Karla Hoffman (George Mason University), Don Kleinmuntz (Kleinmuntz Associates), Sheldon Jacobson (University of Illinois), David Shmoys (Cornell University). The panel discussed successful case studies based on their work, research, and consulting. The panel was recorded, and you can watch it below:

I discussed the Summit on the INFORMS Resoundingly Human podcast. You can listen to it here.

Secretary John McHugh delivers the opening keynote

I introduce the panelists

Panelists David Shmoys, Don Kleinmuntz, Karla Hoffman, Sheldon Jacobson, and Bala Ganesh

I ask the panelists a question.

 

Read my post about last year’s INFORMS Government & Analytics Summit.


It’s National Emergency Medical Services Week #EMSweek2019. Check out my teaching materials about EMS systems.

Yesterday, I blogged about my research in emergency medical service systems.

I have used EMS research in my teaching. I once taught an entire course on public sector operations research. The blog post about this course is here, and it has a lot of materials.

I visited the University of Oklahoma, where I lectured about modeling service networks and focused on location problems using network optimization for public safety (such as EMS). I introduced public safety operations research and discussed several location models for modeling service networks. Read the blog post here.

I visited Oberlin College to deliver the Fuzzy Vance Lecture in Mathematics (see post here). In addition, I gave a lecture to Bob Bosch’s undergraduate optimization course that focused on ambulance location models and modeling integer programs. Read the blog post here.


It’s National Emergency Medical Services Week #EMSweek2019. Check out my papers and presentations about EMS systems.

This week is National Emergency Medical Services Week. I’ve published and spoken extensively about my research on emergency medical services.

Some blog posts about EMS include:

Mike Trick wrote a post about my semi-plenary talk at the 2014 German OR Society conference entitled “Using analytics for emergency response

 

 

Papers include:

  1. McLay, L.A., A Maximum Expected Covering Location Model with Two Types of ServersIIE Transactions 41(8), 730 – 741.
  2. McLay, L.A. and M.E. Mayorga, 2010. Evaluating Emergency Medical Service Performance MeasuresHealth Care Management Science 13(2), 124 – 136.
  3. McLay, L.A., Mayorga, M.E., 2011. Evaluating the Impact of Performance Goals on Dispatching Decisions in Emergency Medical ServiceIIE Transactions on Healthcare Service Engineering 1, 185 – 196.
  4. Chanta, S., Mayorga, M.E., Kurz, M.E., McLay, L.A., 2011. The minimum p-envy location problem: A new model for equitable distribution of emergency resourcesIIE Transactions on Healthcare Systems Engineering 1(2), 101 – 115.
  5. McLay, L.A., Moore, H. 2012. Hanover County Improves Its Response to Emergency Medical 911 CallsInterfaces 42(4), 380-394.
  6. Bandar, D., Mayorga, M.E., McLay, L.A., 2012. Optimal Dispatching Strategies for Emergency Vehicles to Increase Patient SurvivabilityInternational Journal of Operational Research.
  7. McLay, L.A., Brooks, J.P., Boone, E.L., 2012. Analyzing the Volume and Nature of Emergency Medical Calls during Severe Weather Events using Regression MethodologiesSocio-Economic Planning Sciences 46, 55 – 66.
  8. Kunkel, A., McLay, L.A. 2013. Determining minimum staffing levels during snowstorms using an integrated simulation, regression, and reliability modelHealth Care Management Science 16(1), 14 – 26.
  9. McLay, L.A., Mayorga, M.E., 2013. A model for optimally dispatching ambulances to emergency calls with classification errors in patient prioritiesIIE Transactions 45(1), 1—24. This paper was selected as a Best Paper Award for IIE Transactions Focused Issue on Scheduling and Logistics.
  10. Mayorga, M.E., Bandara, D., McLay, L.A., 2013. Districting and dispatching policies for emergency medical service systems to improve patient survivalIIE Transactions on Healthcare Systems Engineering 3(1), 39 – 56.
  11. Toro-Diaz, H., Mayorga, M.E., Chanta, S., McLay, L.A., 2013. Joint location and dispatching decisions for Emergency Medical ServicesComputers & Industrial Engineering 64(4), 917 – 928.
  12. Dreiding, R.A., McLay, L.A., An Integrated Screening Model for Screening Cargo Containers for Nuclear WeaponsEuropean Journal of Operational Research 230, 181 – 189.
  13. Chanta, S., Mayorga, M. E., McLay, L. A., 2014. Improving Rural Emergency Services without Sacrificing Coverage: A Bi-Objective Covering Location Model for EMS SystemsAnnals of Operations Research 221(1), 133 – 159.
  14. Sudtachat, K., Mayorga, M.E., McLay, L.A. 2014. Recommendations for Dispatching Emergency Vehicles under Multi-tiered Response via SimulationInternational Transactions in Operational Research 21(4), 581-617.
  15. Chanta, S., Mayorga, M.E., McLay, L.A., 2014. The minimum p-envy problem with requirement on minimum survival rateComputers & Industrial Engineering 74, 228 – 239.
  16. Bandara, D., Mayorga, M.E., McLay, L.A., 2014. Priority Dispatching Strategies for EMS SystemsThe Journal of the Operational Research Society 65, 572 – 587.
  17. Grannan, B.C., Bastian, N., McLay, L.A. A Maximum Expected Covering Problem for Locating and Dispatching Two Classes of Military Medical Evacuation Air AssetsOperations Research Letters 9, 1511-1531.
  18. Toro-Diaz, H., Mayorga, M.E., McLay, L.A., Rajagopalan, H., Saydem, C., Reducing disparities in large scale emergency medical service systemsJournal of the Operational Research Society 66, 1169-1181. doi:10.1057/jors.2014.83
  19. McLay, L.A., Mayorga, M.E., 2013. A dispatching model for server-to-customer systems that balances efficiency and equityManufacturing & Service Operations Management 15(2), 205 – 200.
  20. Ansari, S., McLay, L.A., Mayorga, M.E., 2015. A Maximum Expected Covering Problem for District DesignTransportation Science 51(1), 376 – 390.
  21. Sudtachat, K., Mayorga, M.E., McLay, L.A., 2016. A Nested-Compliance Table Policy for Emergency Medical Service Systems under RelocationOMEGA 58, 154 – 168.
  22. Ansari, S., Yoon, S., Albert, L. A., 2017. An approximate Hypercube model for public service systems with co-located servers and multiple responseTransportation Research Part E: Logistics and Transportation Review. 103, 143 – 157. DOI: 1016/j.tre.2017.04.013.
  23. Yoon, S., Albert, L. An Expected Coverage Model with a Cutoff Priority QueueHealth Care Management Science 21(4), 517 – 533. DOI: https://doi.org/10.1007/s10729-017-9409-3.
  24. Enayati, S., Mayorga, M., Toro-Diaz, H., Albert, L. 2018. Identifying trade-offs in equity and efficiency for simultaneously optimizing location and multi-priority dispatch of ambulancesInternational Transactions in Operational Research 26, 415 – 438. DOI:1111/itor.12590
  25. Yoon, S. and Albert, L.A., 2018. Dynamic Resource Assignment for Emergency Response with Multiple Types of Vehicles, Submitted to Operations Research, October 2018.
  26. Yoon, S., and Albert, L.A. A dynamic ambulance routing model with multiple response. Submitted to Transportation Research Part E: Logistics and Transportation Review, January 2019.

popular science and math books

Nearly five years ago I wrote a post about mathy popular science books, where I recommended the following books:

  1. In Pursuit of the Traveling Salesman by Bill Cook (An outstanding book about operations research. Read my post here)
  2. Traffic: Why We Drive the Way We Do (and What It Says About Us) by Tom Vanderbilt (read my post here)
  3. Moneyball: The Art of Winning an Unfair Game by Michael Lewis
  4. Scorecasting: The Hidden Influences Behind How Sports are Played and Games are Won by Tobias Moskowitz and Jon Wertheim
  5. How Not to be Wrong: The Power of Mathematical Thinking by Jordan Ellenberg
  6. The Signal and the Noise: Why So Many Predictions Fail — But Some Don’t by Nate Silver

I have been continuing to read popular science and math books. Here are the ones I’ve liked since my last post on this topic.

  1. Who Gets What and Why: by Al Roth (another outstanding book about operations research).
  2. Weapons of Math Destruction by Cathy O’Neil. So good.
  3. Algorithms to Live By by Brian Christian and Tom Griffiths (I wrote a post about this)
  4. Expecting Better: Why the Conventional Pregnancy Wisdom Is Wrong–and What You Really Need to Know by Emily Oster.
  5. Twitter and Tear Gas by Zeynep Tufekci
  6. The Sports Gene by David Epstein
  7. Endure: Mind, Body, and the Curiously Elastic Limits of Human Performance by Alex Hutchinson
  8. Dataclysm by Christian Rudder
  9. Thinking Fast and Slow by Daniel Kahneman.
  10. Nudge: by Richard Thaler and Cass Sunstein.

The books on my reading list for this summer include:

  1. Infinite powers: how calculus reveals the secrets of the universe by Steven Strogatz
  2. Mind and Matter: A Life in Math and Football by John Urschel
  3. Cribsheet by Emily Oster (Finally a book about data-driven parenting!)

What else should I read?


how to change your academic name mid-career

Two years ago, I changed my name as a mid-career associate professor. Was it worth it?

Short answer: yes.

This post is about the process of changing my name on my academic accounts to ensure that people can find me with a new name and can see everything I have published. My fear from the beginning was that no one would know who I am and colleagues would have trouble finding my publications. Two years in, colleagues seem accustomed to my new name.

For more reading, check out my earlier post about the decision to change my name.

Changing my CV

The easy part was changing my CV.  The top of my CV says I am “Laura A. Albert, formerly Laura A. McLay.” My CV has links to my Google scholar page, Researchgate account, ORCID page, and SCOPUS author page so people can find what they are looking for. I put my name in boldface in all of my publications so it’s clear that I was an author. Easy.

Changing my publishing profile

I was concerned that others will find it hard to evaluate my research because the tools we use to do so in academia do not make it easy. Computing an “h-index,” for example, might be non-trivial if the systems used to do so assume that I have published under one name and could underestimate my research impact. I was not yet a full professor when I changed my name, and I was concerned this would affect promotion. Google Scholar allows me to add publications to my account under any name, which helps, but ultimately, I do not know whether anyone will use it (which is why I put links to my Google scholar profile on my CV).

I was able to update my names rather easily on my Google Scholar and ResearchGate, SCOPUS, and ORCID accounts, where I manually add publications across both names and merged author names in my accounts. Publishers get it.

Side note: The issues I raise here apply to everyone, not just people changing their last name. Anyone’s name can appear in different ways across different publications, so SCOPUS, for example, has to merge the names for a single author to correctly compute an h-index. It’s valuable for everyone to keep track of their publication impact because it’s very easy for these systems to miss a few publications. An h-index can only be under-estimated if it splits your publication across multiple author accounts.

Changing my name at the university

I asked staff to adopt my new name and they were wonderful in helping me make my transition.

University policy, on the other hand, made the name change extremely difficult. The UW system adopted a “Preferred name policy” that makes situations like mine more difficult than it should be to navigate. The policy states:

“The goal of the Preferred Name policy is a consistent preferred name experience across University systems and use of one’s preferred name wherever legal name is not absolutely necessary.”

The name change policy was originally designed to reduce fraud from students changing their email name to something else and to support those who go by something other than their first name. These are good goals, but the implementation of the policy meant that users cannot edit their last name in any IT systems. I had planned to change the name I used professionally in between academic years, but the IT systems changed my name when I changed it legally, which was mid-year.

Here is why the inflexible policy was a pain: If a professor planned to get married in September, for example, it would be easier if she preemptively changed her name prior to the beginning of the school year rather than have everyone learn her by her outgoing name and then call her the wrong name for the rest of the year. This type of problem occurs with an inflexible preferred name policy.

The implementation of the preferred name policy left a lot to be desired. I planned for changing my name by specifying a custom preferred name (“Laura Albert McLay”) in August before it changed legally to make what I hoped would be a smooth name change transition. However, I noticed that my preferred name was either not used by some IT systems or truncated by others, omitting the middle name I specified as my preferred name. As a result, not-preferred names showed up frequently in different forms–course catalogs, the online course management tools, teaching evaluations, Office 365 products–and I could not change how my name was displayed. Students inevitably called me by a name I did not prefer.

Changing various online profiles

I discovered that IT systems are not designed to accommodate name changes or email changes that reflect name changes. Sometimes old names and emails show up even after I made a change because they were pulling my email from a shadow database. Some accounts use an email as a login and did not allow me to change my email without having to create a new account. This is poor IT design and highlights the need for diverse teams in tech.

Finally, it was the most work to change my name on frequent flyer and hotel rewards accounts. They required more paperwork and justification than my bank.

What you can do when someone you work with changes their name

Here are some suggestions if you encounter someone who wants to change or is changing their name professionally:

  1. Changing my name was a pain, but it’s a personal decision. It may not be for everyone. If a student, for example, asks your advice prior to a marriage and you don’t feel like you’ve had the right experiences to have this conversation, introduce them to someone who can talk to them about the pros and cons.
  2. When in doubt, ask someone what they prefer to be called. Journalists are wonderful in this regard because it’s their job to get names right. Everyone else needs to take note. One way to bring it up is to say, “I noticed your name is sometimes written down as Laura Albert. How would you like to be addressed?”
  3. Years ago a colleague corrected someone else’s name that changed following her divorce. Without revealing the reason for the change, he simply said, “We’d better correct that because she is going by Jane Doe now,” and did not mention her divorce. I cannot imagine a better response.
  4. I am not a fan of being described as “divorced” in professional settings unless absolutely necessary. My marital status is rarely relevant in professional settings. Additionally, I’ve thought of myself as “single” as opposed to “divorced,” because the latter (“divorced”) defines me in terms of someone else, whereas “single” does not. It’s best to not define women in terms of her personal relationships to men in professional settings.


five posts about motherhood and operations research

Happy Mother’s Day! It’s no secret that I apply operations research to my life. Here are five posts about parenting and operations research.

1. On queueing theory and work-life balence: how role models, having children early in my career, and understanding queueing theory helped me maintain some semblance of balance.

2. The book Algorithms to Live By by Brian Christian and Tom Griffiths features me talking about how I employ the critical path method to get my three daughters to school on time every morning.

3. What the Birthday Problem teaches us about when to have children: insights on congestion in hospitals.

4. I blogged about parenting 11 years ago as an assistant professor after the birth of my second child, when I wrote “I worry more about day care than tenure.” A lot has changed in my life since then (tenure and then promotion to full as well as a third child), but I still vividly remember how the logistics of parenting consumed a lot of my energy.

5. In a post about operations research and parenting, I note that parenthood is not an optimization problem, its a feasibility problem.  There are many ways to be a good parent 🙂