The text establishes how to design, develop, and test different hybrids of multi-objective optimization algorithms. It presents several application areas of the multi-objective optimization algorithms.

Presents a thorough analysis of equations, mathematical models, and mechanisms of multi-objective optimization algorithms. Explores different alternatives of the 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 undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communications engineering, computer science and engineering, and mathematics.