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Swarm Intelligence Algorithms for Circles Packing Problem with Equilibrium Constraints

机译:平衡限制的圆圈包装问题的群体智能算法

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Circles packing problem with equilibrium constraints is difficult to solve due to its NP-hard nature. Aiming at this NP-hard problem, three swarm intelligence algorithms are employed to solve this problem. Particle Swarm Optimization and Ant Colony Optimization has been used for the circular packing problem with equilibrium constraints. In this paper, Artificial Bee Colony Algorithm (ABC) for equilibrium constraints circular packing problem is presented. Then we compare the performances of well-known swarm intelligence algorithms (PSO, ACO, ABC) for this problem. The results of experiment show that ABC is comparatively satisfying because of its stability and applicability.
机译:由于其NP难性,难以解决与均衡限制的圆圈包装问题。 针对这个NP难题,采用了三种群体智能算法来解决这个问题。 粒子群优化和蚁群优化已用于均衡限制的圆形包装问题。 本文介绍了用于平衡约束的人造蜂菌落算法(ABC)循环包装问题。 然后我们比较众所周知的群体智能算法(PSO,ACO,ABC)的表演。 实验结果表明,由于其稳定性和适用性,ABC相对满足。

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