Heterogeneous multiprocessor scheduling with differential evolution

The problem of scheduling a parallel program given by a Directed Acyclic Graph (DAG) of tasks is a well-studied area. We present a new approach which employs Differential Evolution to numerically optimize the priorities of tasks. Our algorithm starts with a number of acceptable solutions, results of different heuristics, and merges them to achieve better one in a small number of function evaluations. The algorithm outperforms both a number of greedy heuristics and a classical genetic algorithm on the most of the program graphs considered in our experiments.

• Type: Conference
• Year: 2005
• Where: CEC
• Authors: Krzysztof Rzadca, Franciszek Seredynski
• Keywords: Artificial Intelligence, CEC 2005, Classical Genetic Algorithm, Directed Acyclic Graph, Greedy Heuristics