This week at the analytics lab have made some great progress with respect to research productivity. We have one major revision re-submitted to an excellent journal. As well as a major collaborative article written to define a new sub-field of study within the area of resilience.
Objective Scaling Ensemble Approach for Integer Linear Programming
Dr. Nicholson and Weili Zhang have just completed a submitted a revision of their work “Objective Scaling Ensemble Approach for Integer Linear Programming” as an original article to INFORMS Journal on Computing (IJOC).
IJOC is a top tier journal that publishes papers in the intersection of operations research (OR) and computer science (CS). The article introduces a new heuristic method for application to IP problems. Weili Zhang is the lead author on this beauty of an idea. In the paper we develop the idea and apply it to a wide variety of linear IP problems: from network design to open-pit mining; from vehicle routing to protein folding. The technique was demonstrated to be competitive with the battery of heuristics used in the best commercial solver software. Hopefully, the reviewers will agree with us!
Defining Resilience Analytics
Dr. Nicholson along with Dr. Kash Barker (OU), Dr. Cornelia Caragea (UNT), Dr. James Lambert (UVA), Dr. Laura McLay (Univ of Wisconsin), Dr. Chris Zobel (Virginia Tech), Dr. Andrea Tapia (Penn State), and Dr. Jose Ramirez-Marquez (Stevens Institute) have collaborated on their first article relating to the recent NSF award. The perspectives paper entitled “Defining Resilience Analytics” has been submitted to Risk Analysis, an official international publication of the Society for Risk Analysis. This is hopefully, the first of many for this team.
Divided Neighborhood Exploration Search for Reverse Engineering the Gene Regulatory Network
Finally, Dr. Nicholson, Dr. Corey Clark (SMU), and Leslie Goodwin (Deloitte Consulting) are finalizing their work on reverse engineering the gene regulatory network (GRN). Credit definitely goes to Leslie Goodwin for her amazing idea and application. The new technique outperforms the current standard in metaheuristic search for inferring GRNs — in both speed and quality. The current version of the paper is near completion and should be submitted by the first of December.
It has been a good week!
Optimal Flow Analysis
This is all in addition to a recent submission to Computers and Industrial Engineering – “Optimal Flow Analysis” another paper by Weili Zhang and Dr. Nicholson. This paper takes a statistical learning approach to evaluating, characterizing, and predict solutions to a traditional optimization problem, the fixed-charge network flow problem. We presented this work at a recent INFORMS conference as well as one of the more promising applications — the paper regarding the application technique is well underway and should be submitted before the end of the year!