human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "the road to vegas guiding the search over neutral networks"):
  Abstract: VEGAS (Varying Evolvability-Guided Adaptive Search) is a new methodology proposed to deal with the neutrality property that frequently appears on combinatorial optimization problems. Its main feature is to consider the whole evaluated solutions of a neutral network rather than the last accepted solution. Moreover, VEGAS is designed to escape from plateaus based on the evolvability of solutions, and on a multi-armed bandit by selecting the more promising solution from the neutral network. Experiments are conducted on NK-landscapes with neutrality. Results show the importance of considering the whole identified solutions from the neutral network and of guiding the search explicitly. The impact of the level of neutrality and of the exploration-exploitation trade-off are deeply analyzed.

Includes members:
  Member "nils a neutrality based iterated local search and its application to flowshop scheduling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the neutrality of flowshop scheduling fitness landscapes")
  Member "on the neutrality of flowshop scheduling fitness landscapes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "nils a neutrality based iterated local search and its application to flowshop scheduling")
  Member "fitness landscape of the cellular automata majority problem view from the olympus":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "nils a neutrality based iterated local search and its application to flowshop scheduling")
  Member "when gravity fails local search topology":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exploiting problem structure in combinatorial landscapes a case study on pure mathematics application")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.NE(Neural and Evolutionary Computing)