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Applied Computational Intelligence and Soft Computing
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Applied Computational Intelligence and Soft Computing
/
2019
/
Article
/
Alg 1
Research Article
Learning Based Genetic Algorithm for Task Graph Scheduling
Algorithm 1
A new task graph scheduling algorithm.
Step
1
:
- Create the initial population (classic chromosomes) as described in Section
3.1
.
Step
2
:
-
While
termination condition has not been satisfied
Do
-
For
each classic chromosome in the current population
Do
- Convert it to the extended structure chromosome (such as Table
2
).
- Enhance chromosome by applying learning operators (reward and penalty) on the chromosome until the
makespan could be less, described in Section
3.4
.
-
Convert
extended chromosome to classic chromosome by removing rows related depth and probability
-
Apply
the standard roulette wheel selection strategy for selecting potentially useful individuals for recombination
-
Apply
the standard two-point crossover operator on processors in two enhanced chromosomes
-
Apply
the standard mutation operator on processors in two enhanced chromosomes
-
Apply
the reuse idle time heuristic on 30% of best chromosomes, described in Section
3.3
.