Multi-objective optimization using hybrid genetic algorithm and cellular learning automata applying to graph partitioning problem

2011 ◽  
Author(s):  
Mehdi Farshbaf ◽  
Mohammad-Reza Feizi-Derakhshi ◽  
Arash Roshanpoor
Keyword(s):  
Genetic Algorithm ◽  
Graph Partitioning ◽  
Learning Automata ◽  
Hybrid Genetic Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Graph Partitioning Problem ◽  
Partitioning Problem ◽  
Cellular Learning Automata

scholarly journals Performance of a genetic algorithm for the graph partitioning problem

2003 ◽  
Vol 38 (11-13) ◽  
pp. 1325-1332 ◽  
Author(s):  
Keiko Kohmoto ◽  
Kengo Katayama ◽  
Hiroyuki Narihisa
Keyword(s):  
Genetic Algorithm ◽  
Graph Partitioning ◽  
Graph Partitioning Problem ◽  
Partitioning Problem

A Multi-Objective Optimization Genetic Algorithm for SOPC Hardware-Software Partitioning

2012 ◽  
Vol 457-458 ◽  
pp. 1142-1148
Author(s):  
Fu Yang ◽  
Liu Xin ◽  
Pei Yuan Guo
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Search Algorithm ◽  
Multi Objective Optimization ◽  
Key Technology ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Partitioning Problem ◽  
System On Programmable Chip ◽  
Software Partitioning

Hardware-software partitioning is the key technology in hardware-software co-design; the results will determine the design of system directly. Genetic algorithm is a classical search algorithm for solving such combinatorial optimization problem. A Multi-objective genetic algorithm for hardware-software partitioning is presented in this paper. This method can give consideration to both system performance and indicators such as time, power, area and cost, and achieve multi-objective optimization in system on programmable chip (SOPC). Simulation results show that the method can solve the SOPC hardware-software partitioning problem effectively.

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