Genetic Algorithms and Fuzzy Multiobjective Optimization

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The book addresses a significant gap in the literature on genetic algorithms by presenting a unified approach to solving both single-objective and multiobjective optimization problems, including those involving fuzzy logic. While many existing works focus on single-objective discrete problems under certainty, this text expands the scope to encompass a broader range of applications. It highlights the evolution and contributions of genetic algorithms since their inception in the 1970s, making it a valuable resource for researchers and practitioners in various fields.