Name
Abstract | ||
|---|---|---|
We present a solution of the multiprocessor scheduling problem. based on applying a relatively new metaheuristic called Generalized Extremal Optimization (GEO). GEO is inspired by a simple coevolutionary model known as Bak-Sneppen model. The model assumes existing of an ecosystem consisting of N species. Evolution in this model is driven by a process in which the weakest species in the ecosystem, together with its nearest neighbors is always forced to mutate. This process shows characteristic of a phenomenon called a punctuated equilibrium which is observed in evolutionary biology. We interpret the multiprocessor scheduling problem in terms of the Bak-Sneppen model and apply the GEO algorithm to solve the problem. We show that the proposed optimization technique is simple and :yet outperforms both genetic algorithm (GA)-based and particle swarm optimization (PSO) algorithm-based approaches to the multiprocessor scheduling problem. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1142/S0129054112400230 | INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE |
Keywords | Field | DocType |
Multiprocessor scheduling problem, generalized extremal optimization, GEO, genetic algorithm, GA, particle swarm optimization, PSO | Particle swarm optimization,Mathematical optimization,Multiprocessor scheduling,Extremal optimization,Punctuated equilibrium,Theoretical computer science,Genetic algorithm,Mathematics,Metaheuristic | Journal |
Volume | Issue | ISSN |
23 | 2 | 0129-0541 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Piotr Switalski | 1 | 12 | 3.08 |
| Franciszek Seredynski | 2 | 366 | 55.06 |