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: "asymptotically optimal algorithms for one to one pickup and delivery problems with applications to transportation systems"
  Abstract: Pickup and delivery problems (PDPs), in which objects or people have to be transported between specific locations, are among the most common combinatorial problems in real-world logistical operations. A widely-encountered type of PDP is the Stacker Crane Problem (SCP), where each commodity/customer is associated with a pickup location and a delivery location, and the objective is to find a minimum-length tour visiting all locations with the constraint that each pickup location and its associated delivery location are visited in immediate, consecutive order. The SCP is NP-Hard and the best known approximation algorithm only provides a 9/5 approximation ratio. In this paper, we examine an embedding of the SCP within a stochastic framework, and our objective is three-fold: First, we describe a large class of algorithms for the SCP, where every member is asymptotically optimal, i.e., it produces, almost surely, a solution approaching the optimal one as the number of pickups/deliveries goes to infinity; moreover, one can achieve computational complexity O(n2+e) within the class, where n is the number of pickup/delivery pairs and e is an arbitrarily small positive constant. Second, we characterize the length of the optimal SCP tour asymptotically. Finally, we study a dynamic version of the SCP, whereby pickup and delivery requests arrive according to a Poisson process, and which serves as a model for large-scale demand-responsive transport (DRT) systems. For such a dynamic counterpart of the SCP, we derive a necessary and sufficient condition for the existence of stable vehicle routing policies, which depends only on the workspace geometry, the distributions of pickup and delivery points, the arrival rate of requests, and the number of vehicles. Our results leverage a novel connection between the Euclidean Bipartite Matching Problem and the theory of random permutations, and, for the dynamic setting, exhibit novel features that are absent in traditional spatially-distributed queueing systems.

Connected through hyperedge HE-1 (induced by source paper "toward fast and optimal robotic pick and place on a moving conveyor"):
  with members:
    - "taming combinatorial challenges in optimal clutter removal tasks"
    - "complexity results and fast methods for optimal tabletop rearrangement with overhand grasps"

Connected through hyperedge HE-2 (induced by source paper "fast high quality dual arm rearrangement in synchronous monotone tabletop setups"):
  with members:
    - "coordinating the motion of labeled discs with optimality guarantees under extreme density"
    - "scalable asymptotically optimal multi robot motion planning"
    - "complexity results and fast methods for optimal tabletop rearrangement with overhand grasps"
    - "characterizing minimum length coordinated motions for two discs"
    - "motion planning for unlabeled discs with optimality guarantees"
    - "on the hardness of unlabeled multi robot motion planning"
    - "efficient multi robot motion planning for unlabeled discs in simple polygons"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"

Connected through hyperedge HE-3 (induced by source paper "complexity results and fast methods for optimal tabletop rearrangement with overhand grasps"):
  with members:
    - "high quality tabletop rearrangement with overhand grasps hardness results and fast methods"
    - "motion planning for unlabeled discs with optimality guarantees"
    - "on the hardness of unlabeled multi robot motion planning"
    - "data driven grasp synthesis a survey"
    - "multi agent path planning and network flow"

Connected through hyperedge HE-4 (induced by source paper "the price of fragmentation in mobility on demand services"):
  with members:
    - "pricing and optimization in shared vehicle systems an approximation framework"
    - "network cournot competition"
    - "price competition in networked markets how do monopolies impact social welfare"
    - "on the role of a market maker in networked cournot competition"

Connected through hyperedge HE-5 (induced by source paper "autonomous vehicle routing in congested road networks"):
  with members:
    - "model predictive control of autonomous mobility on demand systems"
    - "a queueing network approach to the analysis and control of mobility on demand systems"

Connected through hyperedge HE-6 (induced by source paper "congestion aware randomized routing in autonomous mobility on demand systems"):
  with members:
    - "autonomous vehicle routing in congested road networks"
    - "a queueing network approach to the analysis and control of mobility on demand systems"

Connected through hyperedge HE-7 (induced by source paper "towards asymptotically optimal one to one pdp algorithms for capacity 2 vehicles"):
  with members:
    - "a quasi polynomial time approximation scheme for euclidean capacitated vehicle routing"

Connected through hyperedge HE-8 (induced by source paper "routing autonomous vehicles in congested transportation networks structural properties and coordination algorithms"):
  with members:
    - "a queueing network approach to the analysis and control of mobility on demand systems"

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.SY(Systems and Control)