human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "combinatorial optimization problems with uncertain costs and the owa criterion"
  Abstract: In this paper a class of combinatorial optimization problems with uncertain costs is discussed. The uncertainty is modeled by specifying a discrete scenario set containing $K$ distinct cost scenarios. The Ordered Weighted Averaging (OWA for short) aggregation operator is applied to choose a solution. The well-known criteria such as: the maximum, minimum, average, Hurwicz and median are special cases of OWA. By using OWA, the traditional min-max approach to combinatorial optimization problems with uncertain costs, often regarded as too conservative, can be generalized. The computational complexity and approximability of the problem of minimizing OWA for the considered class of problems are investigated and some new positive and negative results in this area are provided. These results remain valid for many important problems, such as network or resource allocation problems.

Connected through hyperedge HE-1 (induced by source paper "approximating multiobjective combinatorial optimization problems with the owa criterion"):
  with members:
    - "using the wowa operator in robust discrete optimization problems"
    - "improved approximation algorithms for the min max selecting items problem"
    - "exact algorithms for owa optimization in multiobjective spanning tree problems"

Connected through hyperedge HE-2 (induced by source paper "an improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems"):
  with members:
    - "a comprehensive review of firefly algorithms"
    - "bat algorithm literature review and applications"

Connected through hyperedge HE-3 (induced by source paper "using the wowa operator in robust discrete optimization problems"):
  with members:
    - "exact algorithms for owa optimization in multiobjective spanning tree problems"
    - "on the approximability of minmax regret network optimization problems"

Question: Please tell me which class the center node 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.DS(Data Structures and Algorithms)