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Improved binary artificial bee colony algorithm Research Articles

Rafet Durgut,rafetdurgut@karabuk.edu.tr

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 8, Pages 1080-1091 doi: 10.1631/FITEE.2000239

Abstract: The (ABC) algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’ food search behavior. Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space, modification is required to apply it to problems. In this study, we modify the ABC algorithm to solve problems and name it the improved binary ABC (IbinABC). The proposed method consists of an update mechanism based on fitness values and the selection of different decision variables. Therefore, we aim to prevent the ABC algorithm from getting stuck in a local minimum by increasing its exploration ability. We compare the IbinABC algorithm with three variants of the ABC and other meta-heuristic algorithms in the literature. For comparison, we use the well-known OR-Library dataset containing 15 problem instances prepared for the uncapacitated facility location problem. Computational results show that the proposed algorithm is superior to the others in terms of convergence speed and robustness. The source code of the algorithm is available at https://github.com/rafetdurgut/ibinABC.

Keywords：人工蜂群；二进制优化；无容量限制的设施选址位置问题（UFLP）

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A simple multi-wave algorithm for the uncapacitated facility location problem

Fred GLOVER, Saïd HANAFI, Oualid GUEMRI, Igor CREVITS

Frontiers of Engineering Management 2018, Volume 5, Issue 4, Pages 451-465 doi: 10.15302/J-FEM-2018038

Abstract: We propose a simple multi-wave algorithm for solving the Uncapacitated Facility Location Problem (UFLP

Keywords： discrete optimization UFLP multi-wave optimization strategic oscillation tabu search