Titlebook: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010); Juan R. González,David Alejandro Pelta,Natalio Kra Book 20101st edit

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Social Target Localization in a Population of Foragers,ronment. In addition to efficiently exploring an area, foragers have to be able to find special targets which are common to the whole population. This work proposes a method to cooperatively perform this particular task. Instead of using local or global localization strategies which can rely on the

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Hybrid Cooperation Models for the Tool Switching Problem, has been tackled in the literature using both complete and heuristic methods, including local-search metaheuristics, population-based methods and hybrids thereof (e.g., memetic algorithms). This work approaches the ToSP using several hybrid cooperative models where spatially-structured agents are e

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Fault Diagnosis in Industrial Systems Using Bioinspired Cooperative Strategies,the Differential Evolution and Ant Colony Optimization algorithms are considered. Both algorithms have been applied to a benchmark problem, the two tanks system. The experiments have considered noisy data in order to compare the robustness of the diagnosis. The preliminary results indicate that the

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A New Metaheuristic Bat-Inspired Algorithm,tough optimization problems. In this paper, we propose a new metaheuristic method, the Bat Algorithm, based on the echolocation behaviour of bats. We also intend to combine the advantages of existing algorithms into the new bat algorithm. After a detailed formulation and explanation of its implement

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,Eagle Strategy Using Lévy Walk and Firefly Algorithms for Stochastic Optimization,bjective functions and constraints. This paper provides a new two-stage hybrid search method, called Eagle Strategy, for stochastic optimization. This strategy intends to combine the random search using Lévy walk with the firefly algorithm in an iterative manner. Numerical studies and results sugges

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