An exceptionally difficult binary quadratic optimization problem with symmetry: a challenge for the largest unsolved QAP instance Tai256c

Abstract

Tai256c is the largest unsolved quadratic assignment problem (QAP) instance in QAPLIB. It is known that QAP tai256c can be converted into a 256 dimensional binary quadratic optimization problem (BQOP) with a single cardinality constraint which requires the sum of the binary variables to be 92. As the BQOP is much simpler than the original QAP, the conversion increases the possibility to solve the QAP. Solving exactly the BQOP, however, is still very difficult. Indeed, a 1.48% gap remains between the best known upper bound (UB) and lower bound (LB) of the unknown optimal value. This paper shows that the BQOP admits a nontrivial symmetry, a property that makes the BQOP very hard to solve. Despite this difficulty, it is imperative to decrease the gap in order to ultimately solve the BQOP exactly. To effectively improve the LB, we propose an efficient BB method that incorporates a doubly nonnegative relaxation, the orbit branching and the isomorphism pruning. With this BB method, a new LB with 1.25% gap is successfully obtained, and computing an LB with 1.0% gap is shown to be still quite difficult. © 2025 Elsevier B.V., All rights reserved.