Multi-Objective Optimization
Multi-Objective Optimization

Author: Gade Pandu Rangaiah

Publisher: World Scientific

Published: 2009

Total Pages: 454

ISBN-13: 9812836527

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Optimization has been playing a key role in the design, planning and operation of chemical and related processes for nearly half a century. Although process optimization for multiple objectives was studied by several researchers back in the 1970s and 1980s, it has attracted active research in the last 10 years, spurred by the new and effective techniques for multi-objective optimization. In order to capture this renewed interest, this monograph presents the recent and ongoing research in multi-optimization techniques and their applications in chemical engineering. Following a brief introduction and general review on the development of multi-objective optimization applications in chemical engineering since 2000, the book gives a description of selected multi-objective techniques and then goes on to discuss chemical engineering applications. These applications are from diverse areas within chemical engineering, and are presented in detail. All chapters will be of interest to researchers in multi-objective optimization and/or chemical engineering; they can be read individually and used in one''s learning and research. Several exercises are included at the end of many chapters, for use by both practicing engineers and students.

Evolutionary Large-Scale Multi-Objective Optimization and Applications
Evolutionary Large-Scale Multi-Objective Optimization and Applications

Author: Xingyi Zhang

Publisher: John Wiley & Sons

Published: 2024-09-11

Total Pages: 358

ISBN-13: 1394178417

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Tackle the most challenging problems in science and engineering with these cutting-edge algorithms Multi-objective optimization problems (MOPs) are those in which more than one objective needs to be optimized simultaneously. As a ubiquitous component of research and engineering projects, these problems are notoriously challenging. In recent years, evolutionary algorithms (EAs) have shown significant promise in their ability to solve MOPs, but challenges remain at the level of large-scale multi-objective optimization problems (LSMOPs), where the number of variables increases and the optimized solution is correspondingly harder to reach. Evolutionary Large-Scale Multi-Objective Optimization and Applications constitutes a systematic overview of EAs and their capacity to tackle LSMOPs. It offers an introduction to both the problem class and the algorithms before delving into some of the cutting-edge algorithms which have been specifically adapted to solving LSMOPs. Deeply engaged with specific applications and alert to the latest developments in the field, it’s a must-read for students and researchers facing these famously complex but crucial optimization problems. The book’s readers will also find: Analysis of multi-optimization problems in fields such as machine learning, network science, vehicle routing, and more Discussion of benchmark problems and performance indicators for LSMOPs Presentation of a new taxonomy of algorithms in the field Evolutionary Large-Scale Multi-Objective Optimization and Applications is ideal for advanced students, researchers, and scientists and engineers facing complex optimization problems.

Embedded Mechatronic Systems
Embedded Mechatronic Systems

Author: Abdelkhalak El Hami

Publisher: ISTE Press - Elsevier

Published: 2019-12-15

Total Pages: 274

ISBN-13: 1785481894

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Mechatronics brings together computer science, mechanics and electronics. It enables us to improve the performances of embedded electronic systems by reducing their weight, volume, energy consumption and cost. Mechatronic equipment must operate without failure throughout ever-increasing service lives. The particularly severe conditions of use of embedded mechatronics cause failure mechanisms which are the source of breakdowns. Until now, these failure phenomena have not been looked at with enough depth to be able to be controlled. Embedded Mechatronic Systems 1, Second Edition presents two methodologies: the statistical approach to the design optimization by reliability and the experimental approach for the characterization of the development of mechatronic systems in operating mode. It also analyzes new analysis tools on the effects of thermal, vibratory, humidity, electric and electromagnetic stresses. Presents a statistical approach to the design optimization by reliability It presents an experimental approach for the characterization of the development of mechatronic systems in operating mode The book analyzes new analysis tools on the effects of thermal, vibratory, humidity, electric and electromagnetic stresses

Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

Author: M.C. Bhuvaneswari

Publisher: Springer

Published: 2014-08-20

Total Pages: 181

ISBN-13: 8132219589

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This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation and operators like crossover, mutation, etc, can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field of VLSI and embedded system design. The book introduces the multi-objective GA and PSO in a simple and easily understandable way that will appeal to introductory readers.