Authors:
Sultan Zeybek
and
Ebubekir Koç
Affiliation:
Fatih Sultan Mehmet Vakif University, Turkey
Keyword(s):
Bees Algorithm, Swarm Intelligence, Artificial Intelligence, Combinatorial Optimization, Local Search, Vantage Point Trees, Nearest Neighbourhood Search.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Life
;
Computational Intelligence
;
Evolutionary Computing
;
Soft Computing
;
Swarm/Collective Intelligence
Abstract:
In this paper, an implementation of vantage point local search procedure for the Bees Algorithm (BA) in
combinatorial domains is presented. In its basic version, the BA employs a local search combined with
random search for both continuous and combinatorial domains. In this paper, a more robust local searching
strategy namely, vantage point procedure is exploited along with random search to deal with complex
combinatorial problems. This paper proposes a hybridization technique which involves the Bee Algorithm
(BA) and a local search technique based on Vantage Point Tree (VPTs) construction. Following a
description of the Vantage Point Bees Algorithm (VPBA), the paper presents the results obtained for several
local search strategies for BA, demonstrating efficiency and robustness of the VPBA.