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Advances in Swarm Intelligence, Part I

. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining;

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Advances in Swarm Intelligence

; and firefly algorithm. Part II: multi-objective optimization; portfolio optimization; community detection; multi-agent systems and swarm;

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Advances in Swarm Intelligence

; and firefly algorithm. Part II: multi-objective optimization; portfolio optimization; community detection; multi-agent systems and swarm;

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Advances in Swarm Intelligence

of swarm intelligence research; novel swarm-based optimization algorithms; swarming behaviour; some swarm intelligence algorithms and their;

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Advances in Swarm Intelligence

of swarm intelligence research; novel swarm-based optimization algorithms; swarming behaviour; some swarm intelligence algorithms and their;

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Swarm Intelligence

mathematical optimization, addressing basic concepts related to swarm intelligence, such as randomness, random walks, and chaos theory. The text then;

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Swarm Intelligence

mathematical optimization, addressing basic concepts related to swarm intelligence, such as randomness, random walks, and chaos theory. The text then;

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Nature-Inspired Computation and Swarm Intelligence

Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization;

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Advances in Swarm and Computational Intelligence

-based optimization algorithms and applications; particle swarm opt8imization; ant colony optimization; artificial bee colony algorithms;

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Advances in Swarm and Computational Intelligence

-based optimization algorithms and applications; particle swarm opt8imization; ant colony optimization; artificial bee colony algorithms;

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Advances in Swarm and Computational Intelligence

-based optimization algorithms and applications; particle swarm opt8imization; ant colony optimization; artificial bee colony algorithms;

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Advances in Swarm Intelligence

Optimization; Particle Swarm Optimization; Ant Colony Optimization; Differential Evolution; Genetic Algorithm and Evolutionary Computation; Fireworks;

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Advances in Swarm Intelligence

selected from 127 submissions. The papers are organized in 12 cohesive topical sections as follows: Swarm intelligence and nature-inspired;

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Swarm Intelligence: Principles, current algorithms and methods

improvements from typical particle swarm optimization (PSO), ant colony optimization (ACO) and fireworks algorithm (FWA) as well as other swarm;

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Advances in Swarm Intelligence

; theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic;

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Swarm Intelligence Algorithms

Swarm intelligence algorithms are a form of nature-based optimization algorithms. Their main inspiration is the cooperative behavior;

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Swarm Intelligence Algorithms

Swarm intelligence algorithms are a form of nature-based optimization algorithms. Their main inspiration is the cooperative behavior;

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Advances in Swarm Intelligence

optimization; particle swarm optimization; ant colony optimization; fireworks algorithms and brain storm optimization; swarm intelligence algorithms;

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Advances in Swarm Intelligence

optimization; particle swarm optimization; ant colony optimization; fireworks algorithms and brain storm optimization; swarm intelligence algorithms;

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Swarm Intelligence Based Optimization

Based Optimization, ICSIBO 2016, held in Mulhouse, France, in June 2016. The 9 full papers presented were carefully reviewed and selected from;

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Swarm Intelligence Algorithms

called swarm intelligence algorithms. These algorithms that use the behavior of simple agents and various ways of cooperation between them, are;

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Intelligent Computing Theories and Application

optimization; soft computing; protein structure and function prediction; advances in swarm intelligence: algorithms and applications; optimization;

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Intelligent Computing Theories and Application

optimization; soft computing; protein structure and function prediction; advances in swarm intelligence: algorithms and applications; optimization;

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Intelligent Computing Methodologies

optimization; soft computing; protein structure and function prediction; advances in swarm intelligence: algorithms and applications; optimization;

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Recent Advances in Swarm Intelligence and Evolutionary Computation

, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as;

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Swarm Intelligence and Bio-Inspired Computation

ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied;

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New Advancements in Swarm Algorithms

. While there are numerous books addressing the most widely known swarm methods, namely ant colony algorithms and particle swarm optimization;

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