human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "A Transformation System for Interactive Reformulation of Design Optimization Strategies"
  Abstract: Automatic design optimization is highly sensitive to problem formulation. The choice of objective function, constraints and design parameters can dramatically impact the computational cost of optimization and the quality of the resulting design. The best formulation varies from one application to another. A design engineer will usually not know the best formulation in advance. In order to address this problem, we have developed a system that supports interactive formulation, testing and reformulation of design optimization strategies. Our system includes an executable, data-flow language for representing optimization strategies. The language allows an engineer to define multiple stages of optimization, each using different approximations of the objective and constraints or different abstractions of the design space. We have also developed a set of transformations that reformulate strategies represented in our language. The transformations can approximate objective and constraint functions, abstract or re-parameterize a search space, or divide an optimization into multiple stages. The system is applicable to design problems in which the artifact is governed by algebraic and ordinary differential equations. We have tested the system on problems of racing yacht and jet engine nozzle design. We report experimental results demonstrating that our reformulation techniques can significantly improve the performance of automatic design optimization. Our research demonstrates the viability of a reformulation methodology that combines symbolic program transformation with numerical experimentation. It is an important first step in a research programme aimed at automating the entire strategy formulation process.

Connected through hyperedge HE-1 (induced by source paper "Program Synthesis and Transformation Techniques for Simpuation, Optimization and Constraint Satisfaction Deductive Synthesis of Numerical"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "Knowledge-Based Re-engineering of Legacy Programs for Robustness in Automated Design"):
  with members:
    - "A Computational Environment for Exhaust Nozzle Design"

Question: Please tell me which class the center node belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Genetic_Algorithms