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Titlebook: Advances in Swarm Intelligence; 5th International Co Ying Tan,Yuhui Shi,Carlos A. Coello Coello Conference proceedings 2014 Springer Intern

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Abner Louis Notkins,Michael B. A. Oldstonexisting heuristics either obtain less competitive solutions or consume too much time. In this paper, a new heuristic named Approximate Muscle guided Beam Search (AMBS) is developed to achieve a good trade-off between solution quality and running time. By combining the approximate muscle with beam se
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John Brady,Lionel Feigenbaum,George Khouryproved method, named IEFWA, which modifies EFWA in two aspects: a new Gaussian explosion operator that enables new sparks to learn from more exemplars in the population and thus improves solution diversity and avoids being trapped in local optima, and a new population selection strategy that enables
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Integrated leisure opportunities,. This paper does not focus on any subbranch, but on the metaheuristics research from a unified view. The population of decision vectors is looked on as an abstract matrix and three novel basic solution generation operations, E[p(i,j)], E[p(c·i)] and E[i, p(c·i+j)], are proposed in this paper. They
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Selected Tools of Ecologic Analysis,omagnetic field lines. Its distinct biology characteristics are useful to design new optimization technology. In this paper, a new bionic optimization algorithm named Magnetotactic Bacteria Moment Migration Algorithm(MBMMA) is proposed. In the proposed algorithm, the moments of a chain of magnetosom
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