Multi-objective Optimization In Computational Intelligence

Multi-objective optimization (MO) is part of computational intelligence research. This work explores the theoretical, as well as performance of MOs on a range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. It also features research on multi-objective optimization techniques, applications, and practices.

Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications.

Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.