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In multimodal optimization, maintaining population diversity is one of the most critical issues in genetic algorithm design. A number of niching techniques have been developed and successfully applied to cope with this problem. For multi-population based parallel genetic algorithms, nevertheless, these approaches are obviously inapplicable, since it is very difficult to obtain global information about...
Parallel Genetic Algorithm (PGA) is used in many practical global optimizations to achieve high speed in convergence. The Island Model Parallel Genetic Algorithm (IMPGA) is very useful. Genetic Algorithms are one of the most powerful search and optimization method when we must solvecomplex and time consuming problems. IMPGA are more flexible than other PGA methods. There are several variables in the...
Multiobjective optimization problems have been widely addressed using evolutionary computation techniques. However, when dealing with more than three conflicting objectives (the so-called many-objective problems), the performance of such approaches deteriorates. The problem lies in the inability of Pareto dominance to provide an effective discrimination. Alternative ranking methods have been successfully...
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