human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Optimal and Asymptotically Optimal Equi-partition of Rectangular Domains via Stripe Decomposition"):
  Abstract: We present an efficient method for assigning any number of processors to tasks associated with the cells of a rectangular uniform grid. Load balancing equi-partition constraints are observed while approximately minimizing the total perimeter of the partition, which corresponds to the amount of interprocessor communication. This method is based upon decomposition of the grid into stripes of "optimal" height. We prove that under some mild assumptions, as the problem size grows large in all parameters, the error bound associated with this feasible solution approaches zero. We also present computational results from a high level parallel Genetic Algorithm that utilizes this method, and make comparisons with other methods. On a network of workstations, our algorithm solves within minutes instances of the problem that would require one billion binary variables in a Quadratic Assignment formulation.

Includes members:
  Member "Genetic Algorithms as Multi-Coordinators in Large-Scale Optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Fast EquiPartitioning of Rectangular Domains using Stripe Decomposition")
  Member "Fast EquiPartitioning of Rectangular Domains using Stripe Decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Genetic Algorithms as Multi-Coordinators in Large-Scale Optimization")
  Member "Minimum-Perimeter Domain Assignment":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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