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: "empirical evaluation of construction heuristics for the multidimensional assignment problem"
  Abstract: The multidimensional assignment problem (MAP) (abbreviated s-AP in the case of s dimensions) is an extension of the well-known assignment problem. The most studied case of MAP is 3-AP, though the problems with larger values of s have also a number of applications. In this paper we consider four fast construction heuristics for MAP. One of the heuristics is new. A modification of the heuristics is proposed to optimize the access to slow computer memory. The results of computational experiments for several instance families are provided and discussed.

Connected through hyperedge HE-1 (induced by source paper "conditional markov chain search for the generalised travelling salesman problem for warehouse order picking"):
  with members:
    - "conditional markov chain search for the simple plant location problem improves upper bounds on twelve korkel ghosh instances"
    - "algorithm configuration learning policies for the quick termination of poor performers"
    - "the generalized traveling salesman problem solved with ant algorithms"
    - "markov chain methods for the bipartite boolean quadratic programming problem"
    - "efficient local search algorithms for known and new neighborhoods for the generalized traveling salesman problem"
    - "lin kernighan heuristic adaptations for the generalized traveling salesman problem"
    - "a memetic algorithm for the generalized traveling salesman problem"

Connected through hyperedge HE-2 (induced by source paper "pattern based approach to the workflow satisfiability problem with user independent constraints"):
  with members:
    - "algorithms for the workflow satisfiability problem engineered for counting constraints"
    - "the bi objective workflow satisfiability problem and workflow resiliency"
    - "tight lower bounds for the workflow satisfiability problem based on the strong exponential time hypothesis"
    - "valued workflow satisfiability problem"
    - "polynomial kernels and user reductions for the workflow satisfiability problem"
    - "iterative plan construction for the workflow satisfiability problem"
    - "parameterized complexity results for exact bayesian network structure learning"
    - "on the parameterized complexity and kernelization of the workflow satisfiability problem"

Connected through hyperedge HE-3 (induced by source paper "design evaluation and analysis of combinatorial optimization heuristic algorithms"):
  with members:
    - "the generalized traveling salesman problem solved with ant algorithms"
    - "a new approach to population sizing for memetic algorithms a case study for the multidimensional assignment problem"
    - "local search heuristics for the multidimensional assignment problem"
    - "a memetic algorithm for the generalized traveling salesman problem"
    - "a memetic algorithm for the multidimensional assignment problem"
    - "generalized traveling salesman problem reduction algorithms"

Connected through hyperedge HE-4 (induced by source paper "a new approach to population sizing for memetic algorithms a case study for the multidimensional assignment problem"):
  with members:
    - "local search heuristics for the multidimensional assignment problem"
    - "a memetic algorithm for the generalized traveling salesman problem"
    - "a memetic algorithm for the multidimensional assignment problem"

Connected through hyperedge HE-5 (induced by source paper "a memetic algorithm for the multidimensional assignment problem"):
  with members:
    - "local search heuristics for the multidimensional assignment problem"

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)