Название: Multi-objective Optimization Techniques: Variants, Hybrids, Improvements, and Applications
Автор: Tarik A. Rashid, Aram Mahmoon Ahmed, Bryar A. Hassan, Zaheer Mudher Yaseen, Seyedali Mirjalili, Nebojsa Bacanin, Sinan Q. Salih
Издательство: CRC Press
Год: 2025
Страниц: 359
Язык: английский
Формат: pdf (true), epub
Размер: 32.4 MB
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. Fuzzy logic, an approach based on degrees of truth rather than strict binary (true/false) values, has been integrated into metaheuristic algorithms to tackle complex optimization problems. This integration introduces a level of uncertainty and ambiguity, allowing for more flexible decision-making processes. In fuzzy metaheuristics, each solution is represented not as a precise value, but rather as a fuzzy set with membership functions indicating the degree to which the solution satisfies certain criteria. By incorporating fuzzy techniques into metaheuristic algorithms, such as Particle Swarm Optimization (PSO), the algorithms gain the ability to handle imprecise and vague information more effectively. 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.