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

phytochemicals

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A Dynamical Game Model for Sustainable Development,real-world problem.A computational model for . (SD) problem, called . (DGSD) is proposed. This model combines ideas from . and . in a new paradigm for adaptive behavior of systems. The actors of SD: . and ., are viewed as evolvable systems. The main aim is to ensure a balanced coevolution of SD acto

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Studying the Influence of the Objective Balancing Parameter in the Performance of a Multi-Objectivearch. In this paper we have studied two different schemes of application for that parameter: keeping it constant, or changing its value during the algorithm running, in order to decide the configuration which yields the best set of solutions. We have done it considering our MOACO algorithm, named hC

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Adaptive Evolutionary Testing: An Adaptive Approach to Search-Based Test Case Generation for Objecton; they have an advantage over their static counterparts in that they are more reactive to the unanticipated particulars of the problem. This paper proposes an adaptive strategy for enhancing Genetic Programming-based approaches to automatic test case generation. The main contribution of this study

GEST

Evolutionary Algorithms for Planar MEMS Design Optimisation: A Comparative Study, multi-objective evolutionary algorithms (MOEA) are used. The literature shows that two main classes of MOEA have been used in MEMS evolutionary design Optimisation, NSGA-II and MOGA-II. However, no one has provided a justification for using either NSGA-II or MOGA-II. This paper presents a comparati

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A Distributed Service Oriented Framework for Metaheuristics Using a Public Standard,nted development platform that enables the installation, support and deployment of components that expose and use services dynamically. Using OSGi in a large research area, like the Heuristic Algorithms, facilitate the creation or modification of algorithms, operators or problems using its features:

growth-factor

Cellular Genetic Algorithm on Graphic Processing Units,). In this paper we describe the design of a parallel Cellular Genetic Algorithm (cGA) on a GPU and then evaluate its performance. Beyond the existing works on masterslave for fitness evaluation, we here implement a cGA exploiting data and instructions parallelism at the population level. Using the

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me, hawks (H) and doves (D), it includes two other strategies based on the property of resources: Possession (P), as the right to occupy or possess what one owns; and Trade (T), as the right to buy and sell ownership. The simulations presented in this chapter describe how evolutionary forces, depend