Titlebook: MICAI 2007: Advances in Artificial Intelligence; 6th Mexican Internat Alexander Gelbukh,ángel Fernando Kuri Morales Conference proceedings

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G–Indicator: An M–Ary Quality Indicator for the Evaluation of Non–dominated Sets based on a few assumptions about the preferences of the decision maker. In order to evaluate the performance of our approach, we build several test cases considering different topologies of the Pareto front. The results are compared with those of another popular metric, the S–metric, showing equal or better performance.

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Handling Constraints in Particle Swarm Optimization Using a Small Population Sizeo state-of-the-art constraint-handling techniques. The number of fitness function evaluations that the proposed approach requires is almost the same (or lower) than the number required by the techniques of the state-of-the-art in the area.

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Conference proceedings 2007modeled human intellectual activity: reasoning, learning, seeing and speaking. Later similar methods were extended to super-complex optimization problems that appear in science, social life and industry. Many methods of Artificial Intelligence are borrowed from nature, where there occur similar supe

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Handling Constraints in Particle Swarm Optimization Using a Small Population Size). The proposed approach uses a reinitialization process for preserving diversity, and does not use a penalty function nor it requires feasible solutions in the initial population. The leader selection scheme adopted is based on the distance of a solution to the feasible region. In addition, a mutat

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