Research on the existence of specific classes of combinatorial matrices such as the Circulant Weighing Matrices CWMs lies in the core of diverse theoretical and computational efforts. Modern metaheuristics have proved to be valuable tools for solving such problems. Recently, parallel Algorithm Portfolios APs composed of established search algorithms and sophisticated resource allocation procedures offered significant improvements in terms of time efficiency and solution quality. The present work aims at shedding further light on the latent quality of parallel APs on solving CWM problems. For this purpose, new AP configurations are considered along with specialized procedures that can enhance their performance. Experimental evaluation is conducted on a computationally restrictive, yet widely accessible, multi-core processor computational environment. Statistical analysis is used to reveal performance trends and extract useful conclusions.
['Ilias S. Kotsireas', 'Panos M. Pardalos', 'Konstantinos E. Parsopoulos', 'Dimitris Souravlias']
On the Solution of Circulant Weighing Matrices Problems Using Algorithm Portfolios on Multi-core Processors