Approximating the minimum quadratic assignment problems
Author(s) -
Refael Hassin,
Asaf Levin,
Maxim Sviridenko
Publication year - 2009
Publication title -
acm transactions on algorithms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.093
H-Index - 57
eISSN - 1549-6333
pISSN - 1549-6325
DOI - 10.1145/1644015.1644033
Subject(s) - combinatorics , mathematics , quadratic equation , bounded function , graph , triangle inequality , permutation (music) , discrete mathematics , mathematical analysis , physics , geometry , acoustics
We consider the well-known minimum quadratic assignment problem. In this problem we are given two n × n nonnegative symmetric matrices A = (aij) and B = (bij). The objective is to compute a permutation π of V = {1,…,n} so that ∑ i,j∈Vi≠j aπ(i),π(j)bi,j is minimized. We assume that A is a 0/1 incidence matrix of a graph, and that B satisfies the triangle inequality. We analyze the approximability of this class of problems by providing polynomial bounded approximations for some special cases, and inapproximability results for other cases.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom