Enhancing Surrogate-Based Optimization Through Parallelization PDF Download
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Author: Frederik Rehbach
Publisher: Springer Nature
ISBN: 3031306090
Category : Technology & Engineering
Languages : en
Pages : 123
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Book Description
This book presents a solution to the challenging issue of optimizing expensive-to-evaluate industrial problems such as the hyperparameter tuning of machine learning models. The approach combines two well-established concepts, Surrogate-Based Optimization (SBO) and parallelization, to efficiently search for optimal parameter setups with as few function evaluations as possible. Through in-depth analysis, the need for parallel SBO solvers is emphasized, and it is demonstrated that they outperform model-free algorithms in scenarios with a low evaluation budget. The SBO approach helps practitioners save significant amounts of time and resources in hyperparameter tuning as well as other optimization projects. As a highlight, a novel framework for objectively comparing the efficiency of parallel SBO algorithms is introduced, enabling practitioners to evaluate and select the most effective approach for their specific use case. Based on practical examples, decision support is delivered, detailing which parts of industrial optimization projects can be parallelized and how to prioritize which parts to parallelize first. By following the framework, practitioners can make informed decisions about how to allocate resources and optimize their models efficiently.
Author: Frederik Rehbach
Publisher: Springer Nature
ISBN: 3031306090
Category : Technology & Engineering
Languages : en
Pages : 123
Get Book Here
Book Description
This book presents a solution to the challenging issue of optimizing expensive-to-evaluate industrial problems such as the hyperparameter tuning of machine learning models. The approach combines two well-established concepts, Surrogate-Based Optimization (SBO) and parallelization, to efficiently search for optimal parameter setups with as few function evaluations as possible. Through in-depth analysis, the need for parallel SBO solvers is emphasized, and it is demonstrated that they outperform model-free algorithms in scenarios with a low evaluation budget. The SBO approach helps practitioners save significant amounts of time and resources in hyperparameter tuning as well as other optimization projects. As a highlight, a novel framework for objectively comparing the efficiency of parallel SBO algorithms is introduced, enabling practitioners to evaluate and select the most effective approach for their specific use case. Based on practical examples, decision support is delivered, detailing which parts of industrial optimization projects can be parallelized and how to prioritize which parts to parallelize first. By following the framework, practitioners can make informed decisions about how to allocate resources and optimize their models efficiently.
Author: Carlos Alberto Velez Quintero
Publisher: CRC Press
ISBN: 1000159329
Category : Technology & Engineering
Languages : en
Pages : 219
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Book Description
A considerable amount of scientific evidence has been collected leading to the conclusion that urban wastewater components should be designed as one integrated system, in order to protect the receiving waters cost-effectively. Moreover, there is a need to optimize the design and operation of the sewerage network and wastewater treatment plant (WwTP) considering the dynamic interactions between them and the receiving waters. This book introduces a method called Model Based Design and Control (MoDeCo) for the optimum design and control of urban wastewater components. The book presents a detailed description of the integration of modelling tools for the sewer, the wastewater treatment plants and the rivers. The complex modelling structure used for the integrated model challenge previous applications of integrated modelling approaches presented in scientific literature. The combination of modelling tools and multi-objective evolutionary algorithms demonstrated in this book represent an excellent tool for designers and managers of urban wastewater infrastructure. This book also presents two alternatives to solve the computing demand of the optimization of integrated systems in practical applications: the use of surrogate modelling tools and the use of cloud computer infrastructure for parallel computing.
Author: Hoai An Le Thi
Publisher: Springer
ISBN: 3030218031
Category : Technology & Engineering
Languages : en
Pages : 1164
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Book Description
This book contains 112 papers selected from about 250 submissions to the 6th World Congress on Global Optimization (WCGO 2019) which takes place on July 8–10, 2019 at University of Lorraine, Metz, France. The book covers both theoretical and algorithmic aspects of Nonconvex Optimization, as well as its applications to modeling and solving decision problems in various domains. It is composed of 10 parts, each of them deals with either the theory and/or methods in a branch of optimization such as Continuous optimization, DC Programming and DCA, Discrete optimization & Network optimization, Multiobjective programming, Optimization under uncertainty, or models and optimization methods in a specific application area including Data science, Economics & Finance, Energy & Water management, Engineering systems, Transportation, Logistics, Resource allocation & Production management. The researchers and practitioners working in Nonconvex Optimization and several application areas can find here many inspiring ideas and useful tools & techniques for their works.
Author: Tamas Terlaky
Publisher: SIAM
ISBN: 1611974682
Category : Mathematics
Languages : en
Pages : 730
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Book Description
Optimization is of critical importance in engineering. Engineers constantly strive for the best possible solutions, the most economical use of limited resources, and the greatest efficiency. As system complexity increases, these goals mandate the use of state-of-the-art optimization techniques. In recent years, the theory and methodology of optimization have seen revolutionary improvements. Moreover, the exponential growth in computational power, along with the availability of multicore computing with virtually unlimited memory and storage capacity, has fundamentally changed what engineers can do to optimize their designs. This is a two-way process: engineers benefit from developments in optimization methodology, and challenging new classes of optimization problems arise from novel engineering applications. Advances and Trends in Optimization with Engineering Applications reviews 10 major areas of optimization and related engineering applications, providing a broad summary of state-of-the-art optimization techniques most important to engineering practice. Each part provides a clear overview of a specific area and discusses a range of real-world problems. The book provides a solid foundation for engineers and mathematical optimizers alike who want to understand the importance of optimization methods to engineering and the capabilities of these methods.
Author: Emiliano Iuliano
Publisher: Springer
ISBN: 331921506X
Category : Technology & Engineering
Languages : en
Pages : 86
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Book Description
Aerodynamic design, like many other engineering applications, is increasingly relying on computational power. The growing need for multi-disciplinarity and high fidelity in design optimization for industrial applications requires a huge number of repeated simulations in order to find an optimal design candidate. The main drawback is that each simulation can be computationally expensive – this becomes an even bigger issue when used within parametric studies, automated search or optimization loops, which typically may require thousands of analysis evaluations. The core issue of a design-optimization problem is the search process involved. However, when facing complex problems, the high-dimensionality of the design space and the high-multi-modality of the target functions cannot be tackled with standard techniques. In recent years, global optimization using meta-models has been widely applied to design exploration in order to rapidly investigate the design space and find sub-optimal solutions. Indeed, surrogate and reduced-order models can provide a valuable alternative at a much lower computational cost. In this context, this volume offers advanced surrogate modeling applications and optimization techniques featuring reasonable computational resources. It also discusses basic theory concepts and their application to aerodynamic design cases. It is aimed at researchers and engineers who deal with complex aerodynamic design problems on a daily basis and employ expensive simulations to solve them.
Author: Hajime Igarashi
Publisher: Elsevier
ISBN: 0323996752
Category : Technology & Engineering
Languages : en
Pages : 384
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Book Description
Topology Optimization and AI-based Design of Power Electronic and Electrical Devices: Principles and Methods provides an essential foundation in the emergent design methodology as it moves towards commercial development in such electrical devices as traction motors for electric motors, transformers, inductors, reactors and power electronics circuits. Opening with an introduction to electromagnetism and computational electromagnetics for optimal design, the work outlines principles and foundations in finite element methods and illustrates numerical techniques useful for finite element analysis. It summarizes the foundations of deterministic and stochastic optimization methods, including genetic algorithm, particle swarm optimization and simulated annealing, alongside representative algorithms. The work goes on to discuss parameter optimization and topology optimization of electrical devices alongside current implementations including magnetic shields, 2D and 3D models of electric motors, and wireless power transfer devices. The work concludes with a lengthy exposition of AI-based design methods, including surrogate models for optimization, deep neural networks, and automatic design methods using Monte-Carlo tree searches for electrical devices and circuits. Assists researchers and design engineers in applying emergent topology design optimization to power electronics and electrical device design, supported by step-by-step methods, heuristic derivation, and pseudocodes Proposes unique formulations of AI-based design for electrical devices using Monte Carlo tree search and other machine learning methods Is richly accompanied by detailed numerical examples and repletes with computational support materials in algorithms and explanatory formulae Includes access to pedagogical videos on topics including the evolutionary process of topology optimization, the distribution of genetic algorithms, and CMA-ES
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1668424096
Category : Computers
Languages : en
Pages : 1575
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Book Description
Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.
Author: Joaquim R. R. A. Martins
Publisher: Cambridge University Press
ISBN: 110898861X
Category : Mathematics
Languages : en
Pages : 653
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Book Description
Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 400 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments.
Author: Thomas Bäck
Publisher: Springer Nature
ISBN: 3030581128
Category : Computers
Languages : en
Pages : 753
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Book Description
This two-volume set LNCS 12269 and LNCS 12270 constitutes the refereed proceedings of the 16th International Conference on Parallel Problem Solving from Nature, PPSN 2020, held in Leiden, The Netherlands, in September 2020. The 99 revised full papers were carefully reviewed and selected from 268 submissions. The topics cover classical subjects such as automated algorithm selection and configuration; Bayesian- and surrogate-assisted optimization; benchmarking and performance measures; combinatorial optimization; connection between nature-inspired optimization and artificial intelligence; genetic and evolutionary algorithms; genetic programming; landscape analysis; multiobjective optimization; real-world applications; reinforcement learning; and theoretical aspects of nature-inspired optimization.
Author: Vasant, Pandian
Publisher: IGI Global
ISBN: 1522529918
Category : Computers
Languages : en
Pages : 948
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Book Description
Modern optimization approaches have attracted an increasing number of scientists, decision makers, and researchers. As new issues in this field emerge, different optimization methodologies must be developed and implemented. The Handbook of Research on Emergent Applications of Optimization Algorithms is an authoritative reference source for the latest scholarly research on modern optimization techniques for solving complex problems of global optimization and their applications in economics and engineering. Featuring coverage on a broad range of topics and perspectives such as hybrid systems, non-cooperative games, and cryptography, this publication is ideally designed for students, researchers, and engineers interested in emerging developments in optimization algorithms.
