| Summary: | 碩士 === 中原大學 === 資訊管理研究所 === 100 === The artificial bee colony algorithm ,a novel algorithm in recent years, has been shown to be superior to Genetic algorithms, Particle Swarm Optimization algorithms, and Differential Evolution algorithm. However,there is still room for its improvement in accuracy and convergence rate; in addition, it also involves the issue in terms of the problem of the algorithm,which is easy to fall into the local optimal solution.
This study proposes a search formula for improved employed bees and onlookers bee, by the use of optimal solution vector as well as individual optimal solution to guide the search direction, and to help search for solutions and the speed of convergence. In the scout bee,adding global optimal solutions and individual optimal solution vector to generate and using it to determine the threshold to avoid the problem of the local optimal solution,can effectively enhance the solution accuracy.
This study consists in three experiments, including comparison with related researches, experimental noise, and non-0 the optimal solution. The main objective of the three experiments verifies the outstanding performance in different experimental environments. Different combination with other algorithms can also be examined in the future.
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