Integrating tabu search and VLSN search to develop enhanced algorithms: A case study using bipartite boolean quadratic programs
This work addresses a gap in empirical studies for BBQP, which has real-life applications, but the approach is incremental as it integrates existing methods.
The authors tackled the bipartite boolean quadratic programming problem (BBQP) by developing heuristic algorithms based on tabu search and VLSN search, achieving solutions better than the best previously known for almost all medium and large benchmark instances.
The bipartite boolean quadratic programming problem (BBQP) is a generalization of the well studied boolean quadratic programming problem. The model has a variety of real life applications; however, empirical studies of the model are not available in the literature, except in a few isolated instances. In this paper, we develop efficient heuristic algorithms based on tabu search, very large scale neighborhood (VLSN) search, and a hybrid algorithm that integrates the two. The computational study establishes that effective integration of simple tabu search with VLSN search results in superior outcomes, and suggests the value of such an integration in other settings. Complexity analysis and implementation details are provided along with conclusions drawn from experimental analysis. In addition, we obtain solutions better than the best previously known for almost all medium and large size benchmark instances.