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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.

Computational intelligence. --- Civil engineering. --- Computational Intelligence. --- Civil Engineering. --- Engineering --- Public works --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Metaheuristics. --- Structural optimization --- Data processing. --- Optimal structural design --- Optimization, Structural --- Optimization of structural systems --- Optimum design of structures --- Optimum structural design --- Optimum structures --- Structures, Optimum design of --- Structural design --- Heuristic algorithms

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From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence. This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering. .

Artificial intelligence. Robotics. Simulation. Graphics --- neuronale netwerken --- fuzzy logic --- cybernetica --- KI (kunstmatige intelligentie) --- AI (artificiële intelligentie)

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Soft computing applications plays a crucial role in civil engineering applications, with engineers striving to create outstanding designs that prioritize safety, aesthetics, cost-efficiency, and environmental considerations. Advanced optimization techniques are especially valuable for complex systems including multi-constraint problems, multi-objective problems and control problems needing iterative processes in solving differential equations. Throughout history, people have used their creativity to enhance designs in everyday tasks, and this is where metaheuristics come into play, drawing inspiration from nature to develop novel algorithms. These artificial intelligence-based algorithms possess distinctive attributes, and leveraging various features from different algorithms can enhance the effectiveness of optimization, improving precision, computational efficiency, and convergence. This book serves as a timely resource, summarizing the latest advancements in civil engineering optimization, encompassing both metaheuristic approaches and emerging trends that integrates artificial intelligence and machine learning techniques to predict optimal solutions, streamlining lengthy optimization processes. The book's chapters cover a wide range of civil engineering applications, with the primary goal being to introduce fundamental concepts and advanced adaptations. This comprehensive resource is designed to provide undergraduates and graduate engineering students with a solid understanding of materials and content, making it a valuable reference for university courses in various civil engineering disciplines. The book will be edited, and the editors will contribute to most of the chapters. Depending on the availability of high-quality papers, the editors may increase their contributions by sharing recent research projects and postgraduate students' theses.

Civil engineering --- Soft computing. --- Data processing. --- Civil engineering. --- Computational intelligence. --- Artificial intelligence. --- Civil Engineering. --- Computational Intelligence. --- Artificial Intelligence.

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This timely book deals with a current topic, i.e. the applications of metaheuristic algorithms, with a primary focus on optimization problems in civil engineering. The first chapter offers a concise overview of different kinds of metaheuristic algorithms, explaining their advantages in solving complex engineering problems that cannot be effectively tackled by traditional methods, and citing the most important works for further reading. The remaining chapters report on advanced studies on the applications of certain metaheuristic algorithms to specific engineering problems. Genetic algorithm, bat algorithm, cuckoo search, harmony search and simulated annealing are just some of the methods presented and discussed step by step in real-application contexts, in which they are often used in combination with each other. Thanks to its synthetic yet meticulous and practice-oriented approach, the book is a perfect guide for graduate students, researchers and professionals willing to applying metaheuristic algorithms in civil engineering and other related engineering fields, such as mechanical, transport and geotechnical engineering. It is also a valuable aid for both lectures and advanced engineering students.

Engineering - General --- Engineering & Applied Sciences --- Civil engineering. --- Mathematical optimization. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Engineering. --- Operations research. --- Decision making. --- Computational intelligence. --- Mechanics. --- Mechanics, Applied. --- Civil Engineering. --- Computational Intelligence. --- Theoretical and Applied Mechanics. --- Operation Research/Decision Theory. --- Engineering --- Public works --- Applied mechanics --- Engineering, Mechanical --- Engineering mathematics --- Classical mechanics --- Newtonian mechanics --- Physics --- Dynamics --- Quantum theory --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Construction --- Industrial arts --- Technology --- Decision making --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Mechanics, applied. --- Operations Research/Decision Theory.

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This timely book deals with a current topic, i.e. the applications of metaheuristic algorithms, with a primary focus on optimization problems in civil engineering. The first chapter offers a concise overview of different kinds of metaheuristic algorithms, explaining their advantages in solving complex engineering problems that cannot be effectively tackled by traditional methods, and citing the most important works for further reading. The remaining chapters report on advanced studies on the applications of certain metaheuristic algorithms to specific engineering problems. Genetic algorithm, bat algorithm, cuckoo search, harmony search and simulated annealing are just some of the methods presented and discussed step by step in real-application contexts, in which they are often used in combination with each other. Thanks to its synthetic yet meticulous and practice-oriented approach, the book is a perfect guide for graduate students, researchers and professionals willing to applying metaheuristic algorithms in civil engineering and other related engineering fields, such as mechanical, transport and geotechnical engineering. It is also a valuable aid for both lectures and advanced engineering students.

Operational research. Game theory --- Mathematical statistics --- Classical mechanics. Field theory --- Applied physical engineering --- Planning (firm) --- Artificial intelligence. Robotics. Simulation. Graphics --- Civil engineering. Building industry --- neuronale netwerken --- fuzzy logic --- cybernetica --- toegepaste mechanica --- besluitvorming --- mathematische modellen --- econometrie --- KI (kunstmatige intelligentie) --- operationeel onderzoek --- ingenieurswetenschappen --- mechanica