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Among all aspects of engineering, design is the most important step in developing a new product. A systematic approach to managing design issues can only be accomplished by applying mathematical optimization methods. Furthermore, due to the practical issues in engineering problems, there are limitations in using traditional methods. As such, stochastic optimization methods such as differential evolution, simulated annealing, and genetic algorithms are preferable in finding solutions in design optimization problems. This book reviews mechanical engineering design optimization using stochastic methods. It introduces students and design engineers to practical aspects of complicated mathematical optimization procedures, and outlines steps for wide range of selected engineering design problems. It shows how engineering structures are systematically designed. Many new engineering design applications based on stochastic optimization techniques in automotive, energy, military, naval, manufacturing process and fluids-heat transfer, are described in the book. For each design optimization problem described, background is provided for understanding the solutions. There are very few books on optimization that include engineering applications. They cover limited applications, and that too of well-known design problems of advanced and niche nature. Common problems are hardly addressed. Thus, the subject has remained fairly theoretical. To overcome this, each chapter in this book is contributed by at least one academic and one industrial expert researcher.
Among all aspects of engineering, design is the most important step in developing a new product. A systematic approach to managing design issues can only be accomplished by applying mathematical optimization methods. Furthermore, due to the practical issues in engineering problems, there are limitations in using traditional methods. As such, stochastic optimization methods such as differential evolution, simulated annealing, and genetic algorithms are preferable in finding solutions in design optimization problems. This book reviews mechanical engineering design optimization using stochastic methods. It introduces students and design engineers to practical aspects of complicated mathematical optimization procedures, and outlines steps for wide range of selected engineering design problems. It shows how engineering structures are systematically designed. Many new engineering design applications based on stochastic optimization techniques in automotive, energy, military, naval, manufacturing process and fluids-heat transfer, are described in the book. For each design optimization problem described, background is provided for understanding the solutions. There are very few books on optimization that include engineering applications. They cover limited applications, and that too of well-known design problems of advanced and niche nature. Common problems are hardly addressed. Thus, the subject has remained fairly theoretical. To overcome this, each chapter in this book is contributed by at least one academic and one industrial expert researcher.
This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the probabilities and expectations involved, the book also shows how to apply approximative solution techniques. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures and differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising in engineering, economics and operations research.
Throughout the past few years, there has been extensive research done on structural design in terms of optimization methods or problem formulation. But, much of this attention has been on the linear elastic structural behavior, under static loading condition. Such a focus has left researchers scratching their heads as it has led to vulnerable structural configurations. What researchers have left out of the equation is the element of seismic loading. It is essential for researchers to take this into account in order to develop earthquake resistant real-world structures. Structural Seismic Design Optimization and Earthquake Engineering: Formulations and Applications focuses on the research around earthquake engineering, in particular, the field of implementation of optimization algorithms in earthquake engineering problems. Topics discussed within this book include, but are not limited to, simulation issues for the accurate prediction of the seismic response of structures, design optimization procedures, soft computing applications, and other important advancements in seismic analysis and design where optimization algorithms can be implemented. Readers will discover that this book provides relevant theoretical frameworks in order to enhance their learning on earthquake engineering as it deals with the latest research findings and their practical implementations, as well as new formulations and solutions.
Optimization methods are perceived to be at the heart of computer methods for designing engineering systems. With these optimization methods, the designer can evaluate more alternatives, resulting in a better and more cost-effective design. This guide describes the use of modern optimization methods with simple yet meaningful structural design examples. Optimum solutions are obtained and, where possible, compared with the solutions obtained using traditional design procedures.
This book explores vegetable fiber composite as an eco-friendly, biodegradable, and sustainable material that has many potential industrial applications. The use of vegetable fiber composite supports the sustainable development goals (SDGs) to utilize more sustainable and greener composite materials, which are also easy to handle and locally easily available with economical production costs. This book presents various types of vegetable fiber composite and its processing methods and treatments to obtain desirable properties for certain applications. The book caters to researchers and students who are working in the field of bio-composites and green materials.
An examination of the various types of human-modeled technology, Advances in Applied Human Modeling and Simulation not only covers the type of models available, but how they can be applied to solve specific problems. These models provide a representation of some human aspects that can be inserted into simulations or virtual environments and facilitate prediction of safety, satisfaction, usability, performance, and sustainability. Topics include: Anthropometry and human functional data Biomechanics, occupational safety, comfort and discomfort Biometric authentications Driving safety and human performance Enhancing human capabilities through aids or training Fuzzy systems and neural computing Human behavior and risk assessment modeling Integrating software with humans and systems International cooperation in education and engineering research Intelligent agents in decision training Intelligent data and text mining Machine learning and human factors Modeling physical aspects of work Monitoring systems and human decision Psychophysiological indicators of emotion Resilience engineering and human reliability Scenario-based performance in distributed enterprises Special populations Sustainability, earth sciences and engineering System-of-systems architecting and engineering Verification and validation Virtual interactive design and assessment The math and science provides a foundation for visualizations that can facilitate decision making by technical experts, management or those responsible for public policy. In considering a systems perspective and decisions that affect performance, these models provide opportunities for an expanded role of engineers and HF/E specialists to meet technical challenges worldwide. They can also be used to improve time-to-market, increase safety and ultimately the effectiveness of an organization. The book focuses on applications of these newly developed models and predictive capabilities useful to human factors and ergonomics engineers, cognitive engineers, human computer interaction engineers, human performance modeling engineers, and students in related fields.
With contributions from an international group of authors with diverse backgrounds, this set comprises all fourteen volumes of the proceedings of the 4th AHFE Conference 21-25 July 2012. The set presents the latest research on current issues in Human Factors and Ergonomics. It draws from an international panel that examines cross-cultural differences, design issues, usability, road and rail transportation, aviation, modeling and simulation, and healthcare.
Ch. 1. Introduction / Gade Pandu Rangaiah -- ch. 2. Formulation and illustration of Luus-Jaakola optimization procedure / Rein Luus -- ch. 3. Adaptive random search and simulated annealing optimizers : algorithms and application issues / Jacek M. Jezowski, Grzegorz Poplewski and Roman Bochenek -- ch. 4. Genetic algorithms in process engineering : developments and implementation issues / Abdunnaser Younes, Ali Elkamel and Shawki Areibi -- ch. 5. Tabu search for global optimization of problems having continuous variables / Sim Mong Kai, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 6. Differential evolution : method, developments and chemical engineering applications / Chen Shaoqiang, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 7. Ant colony optimization : details of algorithms suitable for process engineering / V.K. Jayaraman [und weitere] -- ch. 8. Particle swarm optimization for solving NLP and MINLP in chemical engineering / Bassem Jarboui [und weitere] -- ch. 9. An introduction to the harmony search algorithm / Gordon Ingram and Tonghua Zhang -- ch. 10. Meta-heuristics : evaluation and reporting techniques / Abdunnaser Younes, Ali Elkamel and Shawki Areibi -- ch. 11. A hybrid approach for constraint handling in MINLP optimization using stochastic algorithms / G.A. Durand [und weitere] -- ch. 12. Application of Luus-Jaakola optimization procedure to model reduction, parameter estimation and optimal control / Rein Luus -- ch. 13. Phase stability and equilibrium calculations in reactive systems using differential evolution and tabu search / Adrian Bonilla-Petriciolet [und weitere] -- ch. 14. Differential evolution with tabu list for global optimization : evaluation of two versions on benchmark and phase stability problems / Mekapati Srinivas and Gade Pandu Rangaiah -- ch. 15. Application of adaptive random search optimization for solving industrial water allocation problem / Grzegorz Poplewski and Jacek M. Jezowski -- ch. 16. Genetic algorithms formulation for retrofitting heat exchanger network / Roman Bochenek and Jacek M. Jezowski -- ch. 17. Ant colony optimization for classification and feature selection / V.K. Jayaraman [und weitere] -- ch. 18. Constraint programming and genetic algorithm / Prakash R. Kotecha, Mani Bhushan and Ravindra D. Gudi -- ch. 19. Schemes and implementations of parallel stochastic optimization algorithms application of tabu search to chemical engineering problems / B. Lin and D.C. Miller
The volume presents a collaboration between internationally recognized experts on anti-optimization and structural optimization, and summarizes various novel ideas, methodologies and results studied over 20 years. The book vividly demonstrates how the concept of uncertainty should be incorporated in a rigorous manner during the process of designing real-world structures. The necessity of anti-optimization approach is first demonstrated, then the anti-optimization techniques are applied to static, dynamic and buckling problems, thus covering the broadest possible set of applications. Finally, anti-optimization is fully utilized by a combination of structural optimization to produce the optimal design considering the worst-case scenario. This is currently the only book that covers the combination of optimization and anti-optimization. It shows how various optimization techniques are used in the novel anti-optimization technique, and how the structural optimization can be exponentially enhanced by incorporating the concept of worst-case scenario, thereby increasing the safety of the structures designed in various fields of engineering./a