By Suzan Afacan
I will present the article “OR/MS research in disaster operations management” (Altay and Green III, 2006) this week in the ISyE 823. It will be good opportunity for me to give an overview of this paper in my blog post first.
Even in 20th century, disasters are still big issues for the societies and nations. One of the deadliest example is the 2004 Indian Ocean Tsunami which resulted in the lost of 225,000 people.
Altan and Green reviewed the articles in disaster operations management up to 2003.
It is really surprising that most of the studies in the area are done by researchers in the social sciences from social and psychological point of views.
Before starting to the analysis of articles, let’s take a look at the operational stages of disasters;
- Mitigation: applications to reduce the impact of the disasters,
- Preparedness: activities to make society better prepared for disasters,
- Response: resources to protect the community and its property,
- Recovery: long-term actions to recover from the impacts of the disaster.
There is a great table in which the writers summarize the statistics of the articles on Disaster Operations Managements (DOM).
Take away from the table:
- Authors with an affiliation to the USA published most of the articles,
- Main-stream of DOM starts after the 1990s with one of the possible reason being the declaration of 1990s as the International Decade of Natural Disaster Reduction,
- Mathematical programming (included heuristics) is the method most used in the research,
- Based on the Comprehensive Emergency Management’s four-phase disaster classification: mitigation is the most widely studied, preparedness, response and recovery follow it respectively.
- No one studied humanitarian emergencies (epidemics, war etc.),
- Just one article studied recovery planning published in the OR/MS journals.
There is another classification paper on this topic (Denizel et al., 2003), which presents extended classification interested ones might look at that paper also.
“DOM is by nature multi-organizational.”
The writers suggest that trying to include the ethical factors of the subject in the models is worth consideration. Also, different incident specifications may need different optimality approaches since political issues might potentially hit here again.
“You can lead a horse to water, but you cannot make him drink.”
You may not able to make every stakeholder happy even though you have the best math-programming model.
We can consider the article’s resulting idea:
“More research needs to be published in academic journals to attract the attention of OR/MS researchers to the subject matter.”
Especially, between the DOM stages, recovery planning needs more attention by researchers with the understanding of the interdependencies between critical infrastructures and systems.
Managing the disasters better will help for rapidly recovering after the disasters hit, increasing the readiness level of the community and its resources, protecting society and their properties by decreasing the response time and effective usage of the potential resources.
Blogger’s Note: After I read this article, I have a better understanding of how important the recovery phase after a disaster. I think that I am in a right direction with my current research topic in which I have been modeling the interdependency between infrastructure systems and emergency services while trying to recover the systems with more effective way. Additionally, there are several articles, which I know studied the interdependency of the systems by considering the recovery phase of the disaster. (e.g., Nurre, Sarah G., et al ; 2012)
- Altay, Nezih, and Walter G. Green. “OR/MS research in disaster operations management.” European journal of operational research 175.1 (2006): 475-493.
- Nurre, Sarah G., et al. “Restoring infrastructure systems: An integrated network design and scheduling (INDS) problem.” European Journal of Operational Research 223.3 (2012): 794-806.
- Denizel, Meltem, Behlul Usdiken, and Deniz Tuncalp. “Drift or shift? Continuity, change, and international variation in knowledge production in OR/MS.” Operations Research 51.5 (2003): 711-720.