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Established and Recently Proposed Variants of Particle Swarm Optimization
Abstract
In this chapter, we describe established and recently proposed variants of PSO. Due to the rich PSO literature, the choice among different variants proved to be very difficult. Thus, we were compelled to set some criteria and select those variants that best suit them. For this purpose, we considered the following criteria: 1. Sophisticated inspiration source. 2. Close relationship to the standard PSO. 3. Wide applicability in problems of different types. 4. Performance and theoretical properties. 5. Number of reported applications. 6. Potential for further development and improvements. Thus, we excluded variants based on complicated hybrid schemes that combine other algorithms, where it is not evident which algorithm triggers which effect, as well as over-specialized schemes that refer only to one problem type or instance. Under this prism, we selected the following methods: unified PSO, memetic PSO, composite PSO, vector evaluated PSO, guaranteed convergence PSO, cooperative PSO, niching PSO, TRIBES, and quantum PSO. Albeit possibly omitting an interesting approach, the aforementioned variants sketch a rough picture of the current status in PSO literature, exposing the main ideas and features that constitute the core of research nowadays.
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