Algorithm Portfolio

Algorithm portfolio research focuses on creating and evaluating collections of diverse algorithms to improve performance across a range of tasks, overcoming the limitations of relying on a single best algorithm. Current research emphasizes automated portfolio construction methods, often leveraging techniques like Item Response Theory (IRT) to analyze algorithm strengths and weaknesses across various problem instances, and to identify complementary algorithms for parallel execution. This work is significant because it enables more robust and efficient problem-solving in computationally expensive domains like black-box optimization and multi-objective optimization, leading to improved performance and a deeper understanding of algorithm behavior.