Decision Science in Action

This book explores innovative numerical optimization techniques for addressing complex real-world problems. It covers various applications across multiple fields, making it a valuable resource for researchers and organizations alike.

Decision Science in Action offers valuable insights into a variety of innovative numerical optimization techniques designed to tackle real-world challenges. The book emphasizes the complexity of nonlinear optimization problems, which often cannot be addressed effectively through traditional optimization methods. To fill this gap, it explores the design and application of unconventional numerical optimization strategies, including the creation of benchmark functions and their practical implementation in solving diverse optimization issues.

Spanning twenty chapters, the book delves into a range of intriguing research topics. These include Pi fraction-based optimization for the Pantoja–Bretones–Martin (PBM) antenna benchmarks, the development of benchmark function generators for single-objective robust optimization algorithms, and the convergence properties of gravitational search algorithms applied to linear and quadratic functions. Additionally, it presents an algorithm aimed at the multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes, showcasing the breadth of research in this field.

Furthermore, Decision Science in Action addresses practical applications, such as the seismic analysis of multi-story buildings with optimized damper properties and the use of constrained spider monkey optimization for portfolio optimization. It also investigates the impact of upper body motion on the stability of bipedal robots and introduces an ant colony algorithm for routing alternate-fuel vehicles in complex multi-depot scenarios. This comprehensive examination of numerical optimization not only serves researchers but also benefits organizations across various sectors, including Aerospace, Automotive, Biotechnology, and Finance.