Population-Based Metaheuristics for Tasks Scheduling in Heterogeneous Distributed Systems

2011 ◽  
pp. 321-328 ◽  
Author(s):  
Flavia Zamfirache ◽  
Marc Frîncu ◽  
Daniela Zaharie
Keyword(s):  
Distributed Systems ◽  
Population Based ◽  
Tasks Scheduling ◽  
Heterogeneous Distributed Systems

Adaptive load sharing in heterogeneous distributed systems

1990 ◽  
Vol 9 (4) ◽  
pp. 331-346 ◽  
Author(s):  
Ravi Mirchandaney ◽  
Don Towsley ◽  
John A. Stankovic
Keyword(s):  
Distributed Systems ◽  
Load Sharing ◽  
Heterogeneous Distributed Systems

scholarly journals Generalized swarm intelligence algorithms with domain-specific heuristics

2021 ◽  
Vol 10 (1) ◽  
pp. 157
Author(s):  
P. Matrenin ◽  
V. Myasnichenko ◽  
N. Sdobnyakov ◽  
D. Sokolov ◽  
S. Fidanova ◽  
...  
Keyword(s):  
Swarm Intelligence ◽  
Minimum Distance ◽  
Heuristic Algorithms ◽  
Population Based ◽  
Scheduling Problem ◽  
Domain Specific ◽  
Hybrid Approaches ◽  
Self Organized ◽  
Swarm Algorithms ◽  
Tasks Scheduling

<span lang="EN-US">In recent years, hybrid approaches on population-based algorithms are more often applied in industrial settings. In this paper, we present the approach of a combination of universal, problem-free Swarm Intelligence (SI) algorithms with simple deterministic domain-specific heuristic algorithms. The approach focuses on improving efficiency by sharing the advantages of domain-specific heuristic and swarm algorithms. A heuristic algorithm helps take into account the specifics of the problem and effectively translate the positions of agents (particle, ant, bee) into the problem's solution. And a Swarm algorithm provides an increase in the adaptability and efficiency of the approach due to stochastic and self-organized properties. We demonstrate this approach on two non-trivial optimization tasks: scheduling problem and finding the minimum distance between 3D isomers.</span>

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