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. (2019). "A Bicriterion Approach for Generating Alternatives Using Population-Based Algorithms", WSEAS Transactions on Systems, 18(4), 29-34.

Open Access Download

Keywords
Abstract Complex problems are frequently inundated with incompatible performance requirements and inconsistent performance specifications that can be difficult – if not impossible – to identify at the time of problem formulation. Consequently, it is often advantageous to create a set of dissimilar options that provide distinct approaches to the problem. These disparate alternatives need to be close-to-optimal with respect to the specified objective(s), but remain maximally different from each other in the decision domain. The approach for creating such maximally different solution sets is referred to as modelling-to-generate-alternatives (MGA). This paper provides a new, bicriterion MGA approach that can generate sets of maximally different alternatives using any population-based algorithm.