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 "Fast EquiPartitioning of Rectangular Domains using Stripe Decomposition"):
  Abstract: This paper presents a fast algorithm that provides optimal or near optimal solutions to the minimum perimeter problem on a rectangular grid. The minimum perimeter problem is to partition a grid of size M N into P equal area regions while minimizing the total perimeter of the regions. The approach taken here is to divide the grid into stripes that can be filled completely with an integer number of regions . This striping method gives rise to a knapsack integer program that can be efficiently solved by existing codes. The solution of the knapsack problem is then used to generate the grid region assignments. An implementation of the algorithm partitioned a 1000 1000 grid into 1000 regions to a provably optimal solution in less than one second. With sufficient memory to hold the M N grid array, extremely large minimum perimeter problems can be solved easily.

Includes members:
  Member "Genetic Algorithms as Multi-Coordinators in Large-Scale Optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Optimal and Asymptotically Optimal Equi-partition of Rectangular Domains via Stripe Decomposition")
  Member "Optimal and Asymptotically Optimal Equi-partition of Rectangular Domains via Stripe Decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Minimum-Perimeter Domain Assignment")

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