Name
Title | ||
|---|---|---|
A new hierarchical approach for MOPSO based on dynamic subdivision of the population using Pareto fronts |
Abstract | ||
|---|---|---|
This paper introduces a new hierarchical architecture for multi-objective optimization. Based on the concept of Pareto dominance, the process of implementation of the algorithm consists of two stages. First, when executing a multiobjective Particle S warm Optimization (MOPSO), a ranking operator is applied to the population in a predefined iteration to build an initial archive Using ε-dominance. Second, several runs will be based on a dynamic number of sub-populations. Those populations, having a fixed size, are generated from the Pareto fronts witch are resulted from ranking operator. A comparative study with other algorithms existing in the literature has shown a better performance of our algorithm referring to some most used benchmarks. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICSMC.2010.5641884 | Systems Man and Cybernetics |
Keywords | Field | DocType |
Pareto optimisation,demography,iterative methods,particle swarm optimisation,ε-dominance,MOPSO,Pareto dominance,Pareto fronts,hierarchical approach,multiobjective particle swarm optimization,predefined iteration,Pareto Dominance,Pareto Fronts,dynamic population,multiobjective optimization | Population,Mathematical optimization,Ranking,Computer science,Iterative method,Multi-objective optimization,Subdivision,Operator (computer programming),Artificial intelligence,Pareto principle,Machine learning,Benchmark (computing) | Conference |
ISSN | ISBN | Citations |
1062-922X | 978-1-4244-6586-6 | 1 |
PageRank | References | Authors |
0.61 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raja Fdhila | 1 | 1 | 0.61 |
| Tarek M. Hamdani | 2 | 143 | 16.16 |
| Adel M. Alimi | 3 | 81 | 8.88 |