Publications Database

Welcome to the new Schulich Peer-Reviewed Publication Database!

The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:

  • Faculty Member’s Name;
  • Area of Expertise;
  • Whether the Publication is Open-Access (free for public download);
  • Journal Name; and
  • Date Range.

At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.

If you have any questions or input, please don’t hesitate to get in touch.

 

Search Results

Yeomans, J.S. (2015). "Computing Optimal Food Drying Parameters Using the Firefly Algorithm", GSTF Journal on Computing, 4(1), 40-44.

Abstract This study uses the Firefly Algorithm (FA) for computing process drying parameters for agricultural produce dehydration. In a case study of mushroom dehydration, the functional form of the dehydration model is approximated using a response surface technique and the resulting optimization model is a non-linear goal programming problem. While various alternate calculational approaches are possible, an FA-driven procedure is implemented for computing the solution. For optimization purposes, it has been demonstrated that the FA is more computationally efficient than other such commonly-used metaheuristics as genetic algorithms, simulated annealing, and enhanced particle swarm optimization. Hence, the FA approach is a very computationally efficient procedure. It can be shown that the resulting solution computed for the dehydration process parameters is superior to those from all previous approaches.

Yeomans, J.S. (2014). "Establishing Optimal Dehydration Process Parameters for Papaya By Employing A Firefly Algorithm, Goal Programming Approach", International Journal of Engineering Research and Applications, 4(9), 145-149.

Open Access Download

Abstract This study employs a Firefly Algorithm (FA) to determine the optimal osmotic dehydration parameters for papaya. The functional form of the osmotic dehydration model is established via a standard response surface technique. The format of the resulting optimization model to be solved is a non-linear goal programming problem. While various alternate solution approaches are possible, an FA-driven procedure is employed. For optimization purposes, it has been demonstrated that the FA is more computationally efficient than other such commonly-used metaheuristics as genetic algorithms, simulated annealing, and enhanced particle swarm optimization. Hence, the FA approach is a very computationally efficient procedure. It can be shown that the resulting solution determined for the osmotic process parameters is superior to those from all previous approaches