Multi objective Optimization Techniques: Variants, Hybrids, Improvements, and Applications

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Bol The book addresses the theories and applications of the multi-objective optimization algorithm in a single volume. It further covers advanced modifications of multi-objective optimization algorithms. The book discusses multi-objective optimization for diverse engineering applications. The book establishes how to design, develop, and test different hybrids of multi-objective optimization algorithms. It presents several application areas of multi-objective optimization algorithms. Presents a thorough analysis of equations, mathematical models, and mechanisms of multi-objective optimization algorithms. Explores different alternatives of multi-objective optimization algorithms to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problems. Illustrates how to design, develop, and test different hybrids of multi-objective optimization algorithms. Discusses multi-objective optimization techniques for cloud, fog, and edge computing. Highlights applications of multi-objective optimization in diverse sectors such as engineering, e-healthcare, and scheduling. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, communications engineering, computer science and engineering, and mathematics.

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The book addresses the theories and applications of the multi-objective optimization algorithm in a single volume. It further covers advanced modifications of multi-objective optimization algorithms. The book discusses multi-objective optimization for diverse engineering applications. The book establishes how to design, develop, and test different hybrids of multi-objective optimization algorithms. It presents several application areas of multi-objective optimization algorithms. Presents a thorough analysis of equations, mathematical models, and mechanisms of multi-objective optimization algorithms. Explores different alternatives of multi-objective optimization algorithms to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problems. Illustrates how to design, develop, and test different hybrids of multi-objective optimization algorithms. Discusses multi-objective optimization techniques for cloud, fog, and edge computing. Highlights applications of multi-objective optimization in diverse sectors such as engineering, e-healthcare, and scheduling. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, communications engineering, computer science and engineering, and mathematics.


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  • 9781032589985
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