Marco Castellani – författare

This book considers a range of problems in operations research, which are formulated through various mathematical models such as complementarity, variational inequalities, multiobjective optimization, fixed point problems, noncooperative games and inverse optimization. Moreover, the book subsumes all these models under a common structure that allows them to be formulated in a unique format: the Ky Fan inequality. It subsequently focuses on this unifying equilibrium format, providing a comprehensive overview of the main theoretical results and solution algorithms, together with a wealth of applications and numerical examples. Particular emphasis is placed on the role of nonlinear optimization techniques – e.g. convex optimization, nonsmooth calculus, proximal point and descent algorithms – as valuable tools for analyzing and solving Ky Fan inequalities.

This book considers a range of problems in operations research, which are formulated through various mathematical models such as complementarity, variational inequalities, multiobjective optimization, fixed point problems, noncooperative games and inverse optimization. Moreover, the book subsumes all these models under a common structure that allows them to be formulated in a unique format: the Ky Fan inequality. It subsequently focuses on this unifying equilibrium format, providing a comprehensive overview of the main theoretical results and solution algorithms, together with a wealth of applications and numerical examples. Particular emphasis is placed on the role of nonlinear optimization techniques – e.g. convex optimization, nonsmooth calculus, proximal point and descent algorithms – as valuable tools for analyzing and solving Ky Fan inequalities.

This book considers a range of problems in operations research, which are formulated through various mathematical models such as complementarity, variational inequalities, multiobjective optimization, fixed point problems, noncooperative games and inverse optimization. Moreover, the book subsumes all these models under a common structure that allows them to be formulated in a unique format: the Ky Fan inequality. It subsequently focuses on this unifying equilibrium format, providing a comprehensive overview of the main theoretical results and solution algorithms, together with a wealth of applications and numerical examples. Particular emphasis is placed on the role of nonlinear optimization techniques – e.g. convex optimization, nonsmooth calculus, proximal point and descent algorithms – as valuable tools for analyzing and solving Ky Fan inequalities.

This book offers an extensive guide to understanding, implementing, and applying the Bees Algorithm, a powerful nature-inspired optimisation metaheuristic that mimics the foraging behaviour of honey bees. In today's highly interconnected world, systems have become more difficult to optimise. This book addresses the challenge of solving complex optimisation problems efficiently and effectively by drawing inspiration from the remarkable problem-solving abilities observed in nature. The Bees Algorithm provides an elegant, simple, robust, and adaptable approach to navigate the complexities of high-dimensional, multimodal, or time-varying problems that often stymie traditional optimisation methods. This book offers an in-depth exploration of the algorithm, providing a thorough understanding of its underlying principles and mechanisms. It establishes a mathematical framework for the algorithm, facilitating a clearer insight into its behaviour and performance. Through empirical studies and benchmarks, the book demonstrates the algorithm's effectiveness across a range of optimisation problems. Additionally, it showcases practical applications of the Bees Algorithm in diverse fields such as engineering design, robotics, and manufacturing. Finally, it discusses the latest developments and variants of the algorithm, highlighting its potential for future research and innovation. With its accessible style and step-by-step guidance, this book equips readers—be they researchers, practitioners, or students in computer science, engineering, or optimisation—with the knowledge and tools to leverage the principles of swarm intelligence and biomimicry to solve the real-world optimisation challenges of the new industrial age.

This book offers an extensive guide to understanding, implementing, and applying the Bees Algorithm, a powerful nature-inspired optimisation metaheuristic that mimics the foraging behaviour of honey bees. In today's highly interconnected world, systems have become more difficult to optimise. This book addresses the challenge of solving complex optimisation problems efficiently and effectively by drawing inspiration from the remarkable problem-solving abilities observed in nature. The Bees Algorithm provides an elegant, simple, robust, and adaptable approach to navigate the complexities of high-dimensional, multimodal, or time-varying problems that often stymie traditional optimisation methods. This book offers an in-depth exploration of the algorithm, providing a thorough understanding of its underlying principles and mechanisms. It establishes a mathematical framework for the algorithm, facilitating a clearer insight into its behaviour and performance. Through empirical studies and benchmarks, the book demonstrates the algorithm's effectiveness across a range of optimisation problems. Additionally, it showcases practical applications of the Bees Algorithm in diverse fields such as engineering design, robotics, and manufacturing. Finally, it discusses the latest developments and variants of the algorithm, highlighting its potential for future research and innovation. With its accessible style and step-by-step guidance, this book equips readers—be they researchers, practitioners, or students in computer science, engineering, or optimisation—with the knowledge and tools to leverage the principles of swarm intelligence and biomimicry to solve the real-world optimisation challenges of the new industrial age.

Dieses Buch bietet einen Leitfaden zum Verständnis, zur Implementierung und zur Anwendung des Bienenalgorithmus – einer leistungsstarken, naturinspirierten Optimierungs-Metaheuristik, die das Sammelverhalten von Honigbienen nachahmt. In der heutigen hochgradig vernetzten Welt sind Systeme zunehmend schwer zu optimieren. Dieses Buch widmet sich der Herausforderung, komplexe Optimierungsprobleme zu lösen, indem es sich von den bemerkenswerten Problemlösungsfähigkeiten der Natur inspirieren lässt. Der Bienenalgorithmus stellt einen robusten und anpassungsfähigen Ansatz dar, um die Komplexität multimodaler oder zeitvariabler Probleme zu bewältigen – Probleme, an denen traditionelle Optimierungsmethoden oft scheitern. Das Buch bietet eine tiefgehende Analyse des Algorithmus und vermittelt ein Verständnis seiner zugrunde liegenden Prinzipien und Mechanismen. Es etabliert ein mathematisches Rahmenwerk, das einen Einblick in das Verhalten und die Leistungsfähigkeit des Algorithmus ermöglicht.Anhand empirischer Studien und Benchmarks wird die Effektivität des Algorithmus bei einer Vielzahl von Optimierungsproblemen demonstriert. Darüber hinaus werden praktische Anwendungen des Bienenalgorithmus in verschiedenen Bereichen wie Ingenieurwesen, Robotik und Fertigung vorgestellt. Abschließend werden die neuesten Entwicklungen und Varianten des Algorithmus diskutiert, wobei sein Potenzial für zukünftige Forschung und Innovation hervorgehoben wird.Mit seinem zugänglichen Stil und der schrittweisen Anleitung richtet sich dieses Buch an Forscher, Praktiker und Studierende aus den Bereichen Informatik, Ingenieurwesen und Optimierung. Es vermittelt das nötige Wissen und die Werkzeuge, um die Prinzipien der Schwarmintelligenz und Biomimikry zur Lösung realer Optimierungsprobleme im Zeitalter der Industrie 4.0 zu nutzen.