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Reinforced concrete structures are one of the major structural types and must adhere to design regulation codes. It is ideal to find the best design (section dimension, material type, and amount of reinforcement) with the minimum cost providing the design constraints (design formulation considering loading of structure). Metaheuristic methods inspired by natural phenomena can consider design constraints by combining the analyses of formulation of reinforced concrete structures with an iterative numerical algorithm using several convergence options of random generation of candidate design solutions. Metaheuristic Approaches for Optimum Design of Reinforced Concrete Structures: Emerging Research and Opportunities is a pivotal reference source that focuses on several metaheuristic algorithms and the design of several types of structural members. Additionally, retrofit applications and seismic design issues are considered for readers in earthquake zones. Highlighting a wide range of topics including algorithms, design variables, and retrofit design, this book is ideally designed for architects, engineers, urban designers, government officials, policymakers, researchers, academicians, and students.
This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in application contexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications.
This book is an up-to-date source for computation applications of optimization, prediction via artificial intelligence methods, and evaluation of metaheuristic algorithm with different structural applications. As the current interest of researcher, metaheuristic algorithms are a high interest topic area since advance and non-optimized problems via mathematical methods are challenged by the development of advance and modified algorithms. The artificial intelligence (AI) area is also important in predicting optimum results by skipping long iterative optimization processes. The machine learning used in generation of AI models also needs optimum results of metaheuristic-based approaches. This book is a great source to researcher, graduate students, and bachelor students who gain project about structural optimization. Differently from the academic use, the chapter that emphasizes different scopes and methods can take the interest and help engineer working in design and production of structural engineering projects.
The book covers different aspects of real-world applications of optimization algorithms. It provides insights from the Seventh International Conference on Harmony Search, Soft Computing and Applications held at Virtual Conference, Seoul, South Korea, in February 2022. Harmony search (HS) is one of the most popular metaheuristic algorithms, developed in 2001 by Prof. Joong Hoon Kim and Prof. Zong Woo Geem, that mimics the improvisation process of jazz musicians to seek the best harmony. The book consists of research articles on novel and newly proposed optimization algorithms; the theoretical study of nature-inspired optimization algorithms; numerically established results of nature-inspired optimization algorithms; and real-world applications of optimization algorithms and synthetic benchmarking of optimization algorithms.
Surface texturing has been recognized as a method for enhancing the tribological properties of surfaces for many years. Adding a controlled texture to one of two faces in relative motion can have many positive effects, such as reduction of friction and wear and increase in load capacity. To date, the true potential of texturing has not been realized due to the severe lack of detailed information about the mechanistic functional details of texturing in a tribological situation. Inspiration and Design for Bio-Inspired Surfaces in Tribology: Emerging Research and Opportunities is a pivotal reference source that focuses on surface engineering techniques to mimic biological materials. Highlighting a broad range of topics including bio-mimetics, contact analysis, and thermodynamics, this book is ideally designed for engineers, environmentalists, academicians, researchers, and students.
This book includes the scientific results of the fourth edition of the International Conference on Intelligent Computing and Optimization which took place at December 30–31, 2021, via ZOOM. The conference objective was to celebrate “Compassion and Wisdom” with researchers, scholars, experts and investigators in Intelligent Computing and Optimization worldwide, to share knowledge, experience, innovation—marvelous opportunity for discourse and mutuality by novel research, invention and creativity. This proceedings encloses the original and innovative scientific fields of optimization and optimal control, renewable energy and sustainability, artificial intelligence and operational research, economics and management, smart cities and rural planning, meta-heuristics and big data analytics, cyber security and blockchains, IoTs and Industry 4.0, mathematical modelling and simulation, health care and medicine.
Technology has brought about the age of convenience, but at a hefty cost. As a result of a growing production demand on a global scale, adhesive bonding operations also generate a huge amount of hazardous waste. Adhesive bonding, an integral step in manufacturing across several sectors, is one of many culprits of the unprecedented overproduction and environmental burden of municipal, industrial, and hazardous waste. If a cleaner, greener bonding process is formulated, hazardous waste production can be reined in and the world can be safer. Using Lasers as Safe Alternatives for Adhesive Bonding: Emerging Research and Opportunities is a pivotal reference source that analyzes the new conditions for laser processing in the context of adhesive bonding. The book includes the results of experimental research, giving grounds to believe that laser technology has a future in the preparation of products for bonding. From this research, the book presents conclusions for eliminating poisonous chemicals, a threat to humans and the environment, and the burden of liquid and solid waste. It further outlines limitations and requirements imposed on people, such as the need to use personal protective equipment, to establish specific work procedures to ensure the safety of working with lasers, with a view to the future implementation of laser technology in manufacturing facilities. Featuring coverage of a wide range of topics including static strength, surface preparation, and beam impact, this book is ideally designed for engineers, policymakers, researchers, academicians, and students.
The disciplines of science and engineering rely heavily on the forecasting of prospective constraints for concepts that have not yet been proven to exist, especially in areas such as artificial intelligence. Obtaining quality solutions to the problems presented becomes increasingly difficult due to the number of steps required to sift through the possible solutions, and the ability to solve such problems relies on the recognition of patterns and the categorization of data into specific sets. Predictive modeling and optimization methods allow unknown events to be categorized based on statistics and classifiers input by researchers. The Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering is a critical reference source that provides comprehensive information on the use of optimization techniques and predictive models to solve real-life engineering and science problems. Through discussions on techniques such as robust design optimization, water level prediction, and the prediction of human actions, this publication identifies solutions to developing problems and new solutions for existing problems, making this publication a valuable resource for engineers, researchers, graduate students, and other professionals.
This book covers different aspects of real-world applications of optimization algorithms. It provides insights from the Sixth International Conference on Harmony Search, Soft Computing and Applications held at Istanbul University, Turkey, in July 2020. Harmony Search (HS) is one of the most popular metaheuristic algorithms, developed in 2001 by Prof. Joong Hoon Kim and Prof. Zong Woo Geem, that mimics the improvisation process of jazz musicians to seek the best harmony. The book consists of research articles on novel and newly proposed optimization algorithms; the theoretical study of nature-inspired optimization algorithms; numerically established results of nature-inspired optimization algorithms; and real-world applications of optimization algorithms and synthetic benchmarking of optimization algorithms.
In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner.