A Reinforced Evolution-Based Approach to Multi-Resource Load Balancing
By: Leszek Sliwko
Potential Business Impact:
Improves computer learning by copying nature.
This paper presents a reinforced genetic approach to a defined d-resource system optimization problem. The classical evolution schema was ineffective due to a very strict feasibility function in the studied problem. Hence, the presented strategy has introduced several modifications and adaptations to standard genetic routines, e.g.: a migration operator which is an analogy to the biological random genetic drift.
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