human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "On the maximum quadratic assignment problem"
  Abstract: Quadratic Assignment is a basic problem in combinatorial optimization, which generalizes several other problems such as Traveling Salesman, Linear Arrangement, Dense k Subgraph, and Clustering with given sizes. The input to the Quadratic Assignment Problem consists of two n x n symmetric non-negative matrices W = (wi, j) and D = (di, j). Given matrices W, D, and a permutation π: [n] → [n], the objective function is [EQUATION]. In this paper, we study the Maximum Quadratic Assignment Problem, where the goal is to find a permutation π that maximizes Q(π). We give an O(√n) approximation algorithm, which is the first non-trivial approximation guarantee for this problem. The above guarantee also holds when the matrices W, D are asymmetric. An indication of the hardness of Maximum Quadratic Assignment is that it contains as a special case, the Dense k Subgraph problem, for which the best known approximation ratio a n1/3 (Feige et al. [8]).

When one of the matrices W, D satisfies triangle inequality, we obtain a [EQUATION] approximation algorithm. This improves over the previously bestknown approximation guarantee of 4 (Arkin et al. [4]) for this special case of Maximum Quadratic Assignment.

The performance guarantee for Maximum Quadratic Assignment with triangle inequality can be proved relative to an optimal solution of a natural linear programming relaxation, that has been used earlier in Branch-and-Bound approaches (see eg. Adams and Johnson [1]). It can also be shown that this LP has an integrality gap of [EQUATION] for general Maximum Quadratic Assignment.

Connected through hyperedge HE-1 (induced by source paper "Approximating the minimum quadratic assignment problems"):
  with members:
    - "Embedding paths into trees: VM placement to minimize congestion"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Mathematics