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In this paper we propose an Estimation of Distribution Algorithm (EDA) equipped with Voronoi and local search based on leader for multi-objective optimization. We introduce an algorithm that can keep the balance between the exploration and exploitation using the local information in the searched areas through the global estimation of distribution algorithm. Moreover, the probability model in EDA,...
In this study, we will use chaotic inertia weight into the Black Hole Algorithm (BH) in order to further enhance its global search ability. This study proposes a Chaotic Inertia Weight Black Hole Algorithm (CIWBH) method by using chaotic theory into Black Hole Algorithm. In CIWBH, chaos characteristics are combined with the BH algorithm with the intention of further enhancing its performance. Twenty-three...
In this paper, we propose a cluster-based optimization algorithm. It is a greedy agent-based tribal particle swarm optimization algorithm (GATPSO) which adapts the tribes by removing/generating particles and reconstructing tribal links in order to encourage better tribes to proliferate, and causes reducing the computation cost and preventing local optimal solutions. The proposed approach is applied...
This paper proposes the Real-parameter compact supervision for the Particle Swarm Optimization (RCSPSO) in order to optimize problems with continuous parameters. RCSPSO uses the evolutionary configuration of the Real-valued Compact Genetic Algorithm (RCGA) and the search philosophy of the Particle Swarm Optimization (PSO). As a Compact Evolutionary Algorithms (CEA), RCGA rather than operating on a...
Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. However, it is time-consuming in the encoding process and such drawback renders it impractical for real time applications. The time is mainly spent on the search for the best-match...
Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. However, it is time-consuming in the encoding process and such drawback renders it impractical for real time applications. The time is mainly spent on the search for the best-match...
This paper proposes a novel optimization algorithm called cellular probabilistic optimization algorithms (CPOA) based on the probabilistic representation of solutions for real coded problems. In place of binary integers, the basic unit of information here is a probability density function. This probabilistic coding allows superposition of states for a more efficient algorithm. This probabilistic representation...
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