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Agent-Based Simulations Using Genetic Algorithm Calibration: A Children's Services Application
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DOI：10.1109/ACCESS.2022.3199770.png)
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Abstract
En 中文
With increased pressures and tightening budgets within English Children's Services in the UK, seeking more effective operational and financial management is becoming a more significant topic of discussion. In other sectors, complex data analysis methods provide the aforementioned management improvements through better understanding of current situations leading to better decision making. Currently, investment remains at a slow pace in English Local Authorities due to budget restrictions. In this paper, a potential opportunity is explored with existing publicly available data related to this area. With the help of industry experts, an Agent-Based Model is created to emulate basic Children's Services operations and optimised to fit existing data using NSGA-III. With relatively close matches being achieved with sample authorities, this approach demonstrates promise in advancing analytics capabilities for Children's Services and practical solutions are discussed. With this presented work, it is shown that further expansion and exploration into real-world applications is warranted.
Keywords:
Data models
Local government
Analytical models
Genetic algorithms
Calibration
Predictive models
Machine learning
Agent-based modeling
Social factors
Data analysis
Agent-based model
calibration
children's services
data analysis
genetic algorithm
social care