Vectorized candidate set selection for parallel ant colony optimization

Peake, Joshua, Amos, Martyn, Yiapanis, Paraskevas and Lloyd, Huw (2018) Vectorized candidate set selection for parallel ant colony optimization. In: GECCO '18 - Genetic and Evolutionary Computation Conference, 15th - 19th July 2018, Kyoto, Japan.

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Ant Colony Optimization (ACO) is a well-established nature-inspired heuristic, and parallel versions of the algorithm now exist to take advantage of emerging high-performance computing processors. However, careful attention must be paid to parallel components of such implementations if the full benefit of these platforms is to be obtained. One such component of the ACO algorithm is next node selection, which presents unique challenges in a parallel setting. In this paper, we present a new node selection method for ACO, Vectorized Candidate Set Selection (VCSS), which achieves significant speedup over existing selection methods on a test set of Traveling Salesman Problem instances.

Item Type: Conference or Workshop Item (Paper)
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 18 Sep 2018 11:41
Last Modified: 11 Oct 2019 19:15

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