When algorithms use data generated by human beings, they inherit the errors stemming from human biases which likely diminishes their performance. We examine the design and value of a bias-aware linear classification algorithm that accounts for bias in input data, using breast cancer diagnosis as...

The combined scheduling of hydro, thermal and hybrid energy (i.e., wind and solar) is attracting more and more attention nowadays. This paper explores the contribution of renewable energy sources in the traditional hydrothermal scheduling problem in order to overcome the prevailing issues like...

This study introduces the problem of minimizing average relative percentage of imbalance (ARPI) with sequence-dependent setup times in a parallel-machine environment. A mathematical model that minimizes ARPI is proposed. Some heuristics, and two metaheuristics, an ant colony optimization...