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Dynamic Heterogeneous Multi-Population Cultural Algorithm (D-HMP-CA) is a novel optimization algorithm which presents an effective as well as efficient performance to solve large scale global optimization problems. It incorporates dynamic decomposition techniques in order to divide problem dimensions among its local CAs. The variable interactions is not considered in the incorporated dynamic decomposition...
Dynamic multi-objective optimisation problems have more than one objective with at least one objective that changes over time. Previous studies indicated that different knowledge sharing strategies increase the performance of the dynamic vector evaluated particle swarm optimisation (DVEPSO) algorithm in different dynamic environments. Therefore, this paper investigates the performance of the DVEPSO...
In this paper, a SOM (self organizing map)-based approach to task assignment of multi-robots in 3-D dynamic environments is proposed. This approach intends to mimic the operating mechanism of biological neural systems, and integrates the advantages and characteristics of biological neural systems. It is capable of dynamically planning the paths of multi-robots in 3-D environments under uncertain situations,...
In this article we approach the problem of distributed agreement in multi-agent systems using asynchronous particle swarm optimization (PSO) with dynamic neighborhood. The agents are considered as PSO particles which are assumed to have time-dependent neighborhoods, operate asynchronously and incur time delays during information exchange. The performance of the PSO based agreement algorithm is verified...
In view of the existing polygonal approximation algorithm of digital curves can't effectively solve the problem of polygonal approximation constrained by the offset direction, this paper proposes an algorithm of polygonal approximation constrained by the offset direction. First, the offset polygon of the original digital curve is calculated under the control of offset direction and distance. Second,...
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