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A hybrid swarm intelligence based particle-bee algorithm for construction site layout optimization

机译:基于混合群智能的工蜂布局优化算法

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The construction site layout (CSL) design presents a particularly interesting area of study because of its relatively high level of attention to usability qualities, in addition to common engineering objectives such as cost and performance. However, it is difficult combinatorial optimization problem for engineers. Swarm intelligence (SI) was very popular and widely used in many complex optimization problems which was collective behavior of social systems such as honey bees (bee algorithm, BA) and birds (particle swarm optimization, PSO). This study proposed an optimization hybrid swarm algorithm namely particle-bee algorithm (PBA) based on a particular intelligent behavior of honey bee and bird swarms by integrates theirs advantages. This study compares the performance of PBA with that of BA and PSO for hypothetical construction engineering of CSL problems. The results show that the performance of PBA is comparable to those of the mentioned algorithms and can be efficiently employed to solve those hypothetical CSL problems with high dimensionality.
机译:施工现场布局(CSL)设计是一个特别有趣的研究领域,因为它除了对成本和性能等通用工程目标外,对可用性质量的关注也相对较高。然而,对于工程师而言,这是困难的组合优化问题。群智能(SI)非常流行,并广泛用于许多复杂的优化问题,这些问题是社交系统的集体行为,例如蜜蜂(蜜蜂算法,BA)和鸟类(粒子群优化,PSO)。本研究结合蜜蜂和鸟类群的特殊智能行为,提出了一种优化的混合群算法,即粒子蜂算法(PBA)。本研究比较了假设的CSL问题施工工程中PBA,BA和PSO的性能。结果表明,PBA的性能与上述算法相当,可以有效地解决那些假设的CSL高维问题。

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