Duc Truong Pham

This book illustrates the main characteristics, challenges and optimisation requirements of robotic disassembly. It provides a comprehensive insight on two crucial optimisation problems in the areas of robotic disassembly through a group of unified mathematical models. The online and offline optimisation of the operational sequence to dismantle a product, for example, is represented with a list of conflicting objectives and constraints. It allows the decision maker and the robots to match the situation automatically and efficiently. To identify a generic solution under different circumstances, classical metaheuristics that can be used for the optimisation of robotic disassembly are introduced in detail. A flexible framework is then presented to implement existing metaheuristics for sequence planning and line balancing in the circumstance of robotic disassembly. Optimisation of Robotic Disassembly for Remanufacturing provides practical case studies on typicalproduct instances to help practitioners design efficient robotic disassembly with minimal manual operation, and offers comparisons of the state-of-the-art metaheuristics on solving the key optimisation problems. Therefore, it will be of interest to engineers, researchers, and postgraduate students in the area of remanufacturing.

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 illustrates the main characteristics, challenges and optimisation requirements of robotic disassembly. It provides a comprehensive insight on two crucial optimisation problems in the areas of robotic disassembly through a group of unified mathematical models. The online and offline optimisation of the operational sequence to dismantle a product, for example, is represented with a list of conflicting objectives and constraints. It allows the decision maker and the robots to match the situation automatically and efficiently. To identify a generic solution under different circumstances, classical metaheuristics that can be used for the optimisation of robotic disassembly are introduced in detail. A flexible framework is then presented to implement existing metaheuristics for sequence planning and line balancing in the circumstance of robotic disassembly. Optimisation of Robotic Disassembly for Remanufacturing provides practical case studies on typicalproduct instances to help practitioners design efficient robotic disassembly with minimal manual operation, and offers comparisons of the state-of-the-art metaheuristics on solving the key optimisation problems. Therefore, it will be of interest to engineers, researchers, and postgraduate students in the area of remanufacturing.