Evolutionary Algorithms (EAs) are well-known optimization approaches to cope with non-linear, complex problems. These population-based algorithms, however, suffer from a general we...
Shahryar Rahnamayan, Hamid R. Tizhoosh, Magdy M. A...
This paper emphasizes the necessity of formally bringing qualitative and quantitative criteria of ergonomic design together, and provides a novel complementary design framework wit...
Alexandra Melike Brintrup, Jeremy Ramsden, Hideyuk...
Many areas in power systems require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality...
Y. del Valle, Ganesh K. Venayagamoorthy, Salman Mo...
This paper presents a genetic algorithmic approach to the shortest path (SP) routing problem. Variable-length chromosomes (strings) and their genes (parameters) have been used for ...
Abstract--This paper contains a modern vision of the parallelization techniques used for evolutionary algorithms (EAs). The work is motivated by two fundamental facts: first, the d...