A Modification Artificial Bee Colony Algorithm for Optimization Problems
Abstract
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Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. Various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization probl
This paper proposes a new artificial bee colony algorithm with quantum theory and the chaotic local search strategy (QCABC), and uses it to solve the optimal power flow (OPF) problem. Under the quantum computing theory, the QCABC algorithm encodes each individual with quantum bit
Artificial bee colony optimization (ABC) is a fast and robust algorithm for global optimization. It has been widely used in many areas including mechanical engineering. Biogeography -Based Optimizat ion (BBO) is a new biogeography inspired algorithm. It mainly uses the biogeograp
Artificial bee colony (ABC) algorithm is one of the popular swarm intelligence algorithms. ABC has been developed by being inspired foraging and waggle dance behaviors of real bee colonies in 2005. Since its invention in 2005, many ABC models have been proposed in order to solve
This paper propose a new mixture method called Quantum Artificial Bee Colony (QABC) algorithm. QABC is based on some quantum computing concepts, such as qubits and superposition of states. In QABC these quantum concepts are applied on Artificial Bee Colony (ABC) algorithm. ABC is