An iterated greedy algorithm for the binary quadratic programming problem
Fubito Toyama, Kenji Shoji, Hiroshi Mori, Juichi Miyamichi · 2012
The binary quadratic programming problem (BQP) is an NP-hard problem and has a large number of applications. In this paper, an iterated greedy algorithm with k-opt local search (IGKLS) is proposed for the BQP. Iterated greedy (IG) algorithm has already been applied to a variety of optimization problems, and shown to be simple but with excellent search performance. The proposed iterated greedy algorithm consists of two central phases, destruction and construction phases. As a local search algorithm, k-opt local search is applied after the construction phase. The computational results showed that the proposed iterated greedy algorithm outperformed state-of-the-art methods for huge size BQP instances.