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Adaptive inertia weight particle swarm algorithm

Authors: Thakorn Chatchaisathaporn;

Adaptive inertia weight particle swarm algorithm

Abstract

An Optimum Communication Spanning Tree (OCST) problem is a problem of finding a spanning tree of minimum total communication cost satisfying a given set of requirements of communication. The popular technique for solving OCST problem is to use the heuristic algorithm. The heuristic approach does successfully obtain good solutions in a reasonable computational time. The particle swarm optimization-based (PSO) algorithm is one of the heuristic algorithms for optimization problems. In this work, we extend the concept of the particle swarm optimization-based (PSO) algorithm for the OCST problem proposed by Hoang et al. by combining the concept of adaptive inertia weight strategy to the velocity update step. We summarize the effect of the adaptive inertia weight over the proposed algorithm. In addition, we also introduce a new pattern of population initialization. Our proposed algorithm yields a better solution quality.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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