- Table View
- List View
Optimization in Green Sustainability and Ecological Transition: ODS, Ischia, Italy, September 4–7, 2023 (AIRO Springer Series #12)
by Maurizio Bruglieri Paola Festa Giusy Macrina Ornella PisacaneThis book collects selected contributions of the “Optimization and Decision Science - ODS2023” international conference on the theme of optimization in green sustainability and ecological transition. ODS2023 was held in Ischia, 4–7 September 2023, and was organized by AIRO, the Italian Operations Research Society. The book offers new and original contributions on operations research, optimization, decision science, and prescriptive analytics from both a methodological and applied perspectives with a special focus on SDG related topics.It provides a state-of-the art on problem models and solving methods to address a widely class of real-world problems, arising in different application areas such as logistics, transportation, manufacturing, health, ICT and mobile networks, and emergency/disaster management. In addition, the scientific works collected in this book aim at providing significant contributions in the themes of sustainability, traffic and pollution reductions, and energy management.This book is aimed primarily at researchers and Ph.D. students in the Operations Research community. However, due to its interdisciplinary contents, this book is of high interest also for students and researchers from other disciplines, including artificial intelligence, computer sciences, finance, mathematics, and engineering as well as for practitioners facing complex decision-making problems in logistics, manufacturing production, and services.
Optimization in Machine Learning and Applications (Algorithms for Intelligent Systems)
by Suresh Chandra Satapathy Anand J. KulkarniThis book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.
Optimization in Practice with MATLAB® for Engineering Students and Professionals
by Achille MessacOptimization in Practice with MATLAB® provides a unique approach to optimization education. It is accessible to both junior and senior undergraduate and graduate students, as well as industry practitioners. It provides a strongly practical perspective that allows the student to be ready to use optimization in the workplace. It covers traditional materials, as well as important topics previously unavailable in optimization books (e. g. , Numerical Essentials - for successful optimization). Written with both the reader and the instructor in mind, Optimization in Practice with MATLAB® provides practical applications of real-world problems using MATLAB®, with a suite of practical examples and exercises that help the students link the theoretical, the analytical, and the computational in each chapter. Additionally, supporting MATLAB® m-files are available for download via www. cambridge. org. messac. Lastly, adopting instructors will receive a comprehensive solution manual with solution codes along with lectures in PowerPoint with animations for each chapter, and the text's unique flexibility enables instructors to structure one- or two-semester courses.
Optimization, Learning Algorithms and Applications: 4th International Conference, OL2A 2024, Tenerife, Spain, July 24–26, 2024, Proceedings, Part I (Communications in Computer and Information Science #2280)
by Ana I. Pereira Florbela P. Fernandes João P. Coelho João P. Teixeira José Lima Maria F. Pacheco Rui P. Lopes Santiago T. ÁlvarezThis two-volume set, CCIS 2280 and CCIS 2281, constitutes the proceedings of the 4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024, held in Tenerife, Spain, in July 2024. The 41 papers presented here were carefully reviewed and selected from 105 submissions. They have been organized in the two volumes under the following topical sections:- Part I: Learning Algorithms in Engineering Education; Machine Learning; Deep Learning; Optimization in the SDG context. Part II: Optimization in Control Systems Design; Optimization.
Optimization, Learning Algorithms and Applications: 4th International Conference, OL2A 2024, Tenerife, Spain, July 24-26, 2024, Proceedings, Part II (Communications in Computer and Information Science #2281)
by Ana I. Pereira Florbela P. Fernandes João P. Coelho João P. Teixeira José Lima Maria F. Pacheco Rui P. Lopes Santiago T. ÁlvarezThis two-volume set, CCIS 2280 and CCIS 2281, constitutes the proceedings of the 4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024, held in Tenerife, Spain, in July 2024. The 41 papers presented here were carefully reviewed and selected from 105 submissions. They have been organized in the two volumes under the following topical sections:- Part I: Learning Algorithms in Engineering Education; Machine Learning; Deep Learning; Optimization in the SDG context. Part II: Optimization in Control Systems Design; Optimization.
Optimization, Learning Algorithms and Applications: First International Conference, OL2A 2021, Bragança, Portugal, July 19–21, 2021, Revised Selected Papers (Communications in Computer and Information Science #1488)
by Ana I. Pereira Florbela P. Fernandes João P. Coelho João P. Teixeira Maria F. Pacheco Paulo Alves Rui P. LopesThis book constitutes selected and revised papers presented at the First International Conference on Optimization, Learning Algorithms and Applications, OL2A 2021, held in Bragança, Portugal, in July 2021. Due to the COVID-19 pandemic the conference was held online. The 39 full papers and 13 short papers were thoroughly reviewed and selected from 134 submissions. They are organized in the topical sections on optimization theory; robotics; measurements with the internet of things; optimization in control systems design; deep learning; data visualization and virtual reality; health informatics; data analysis; trends in engineering education.
Optimization, Learning Algorithms and Applications: Second International Conference, OL2A 2022, Póvoa de Varzim, Portugal, October 24-25, 2022, Proceedings (Communications in Computer and Information Science #1754)
by Ana I. Pereira Andrej Košir Florbela P. Fernandes Maria F. Pacheco João P. Teixeira Rui P. LopesThis book constitutes the proceedings of the Second International Conference on Optimization, Learning Algorithms and Applications, OL2A 2022, held in Bragança, Portugal, in October 2022. The 53 full papers and 3 short papers were thoroughly reviewed and selected from 145 submissions. They are organized in the topical sections on Machine and Deep Learning; Optimization; Artificial Intelligence; Optimization in Control Systems Design; Measurements with the Internet of Things; Trends in Engineering Education; Advances and Optimization in Cyber-Physical Systems; and Computer vision based on learning algorithms.
Optimization, Learning Algorithms and Applications: Third International Conference, OL2A 2023, Ponta Delgada, Portugal, September 27–29, 2023, Revised Selected Papers, Part II (Communications in Computer and Information Science #1982)
by Ana I. Pereira Armando Mendes Florbela P. Fernandes Maria F. Pacheco João P. Coelho José LimaThis two-volume set CCIS 1981 and 1982 constitutes the refereed post-conference proceedings of the Third International Conference on Optimization, Learning Algorithms and Applications, OL2A 2023, held in Ponta Delgada, Portugal, in September 2023.The 66 revised full papers presented in these proceedings were carefully reviewed and selected from 162 submissions. The papers are organized in the following topical sections:Volume I:Machine learning; learning algorithms in engineering education; machine learning and data analysis in internet of things; optimization; optimization in the SDG context.Volume II:Computer vision based on learning algorithms; machine learning and AI in robotics; optimization in control systems design.
Optimization, Learning Algorithms and Applications: Third International Conference, OL2A 2023, Ponta Delgada, Portugal, September 27–29, 2023, Revised Selected Papers, Part I (Communications in Computer and Information Science #1981)
by Ana I. Pereira Armando Mendes Florbela P. Fernandes Maria F. Pacheco João P. Coelho José LimaThis two-volume set CCIS 1981 and 1982 constitutes the refereed post-conference proceedings of the Third International Conference on Optimization, Learning Algorithms and Applications, OL2A 2023, held in Ponta Delgada, Portugal, in September 2023.The 66 revised full papers presented in these proceedings were carefully reviewed and selected from 162 submissions. The papers are organized in the following topical sections:Volume I:Machine learning; learning algorithms in engineering education; machine learning and data analysis in internet of things; optimization; optimization in the SDG context.Volume II:Computer vision based on learning algorithms; machine learning and AI in robotics; optimization in control systems design.
Optimization, Learning, and Control for Interdependent Complex Networks (Advances in Intelligent Systems and Computing #1123)
by M. Hadi AminiThis book focuses on a wide range of optimization, learning, and control algorithms for interdependent complex networks and their role in smart cities operation, smart energy systems, and intelligent transportation networks. It paves the way for researchers working on optimization, learning, and control spread over the fields of computer science, operation research, electrical engineering, civil engineering, and system engineering. This book also covers optimization algorithms for large-scale problems from theoretical foundations to real-world applications, learning-based methods to enable intelligence in smart cities, and control techniques to deal with the optimal and robust operation of complex systems. It further introduces novel algorithms for data analytics in large-scale interdependent complex networks. • Specifies the importance of efficient theoretical optimization and learning methods in dealing with emerging problems in the context of interdependent networks • Provides a comprehensive investigation of advance data analytics and machine learning algorithms for large-scale complex networks • Presents basics and mathematical foundations needed to enable efficient decision making and intelligence in interdependent complex networks M. Hadi Amini is an Assistant Professor at the School of Computing and Information Sciences at Florida International University (FIU). He is also the founding director of Sustainability, Optimization, and Learning for InterDependent networks laboratory (solid lab). He received his Ph.D. and M.Sc. from Carnegie Mellon University in 2019 and 2015 respectively. He also holds a doctoral degree in Computer Science and Technology. Prior to that, he received M.Sc. from Tarbiat Modares University in 2013, and the B.Sc. from Sharif University of Technology in 2011.
Optimization Methodologies for the Automatic Design of Switched-Capacitor Filter Circuits for IoT Applications (Synthesis Lectures on Engineering, Science, and Technology)
by Hugo Serra Rui Santos-Tavares Nuno PaulinoThis book discusses the design of switched-capacitor filters in deep-submicron CMOS technologies. The authors describe several topologies for switched-capacitor filter circuits that do not require high-gain high-bandwidth amplifiers. Readers will also learn two analysis methodologies that can be implemented efficiently in software and integrated into optimization environments for the automation of design for switched-capacitor filters. Although the optimization examples discussed utilize low gain amplifiers, the demonstrated methodologies can also be used for conventional, high-gain high-bandwidth amplifiers.
Optimization Methods for Product and System Design (Engineering Optimization: Methods and Applications)
by Anand J. KulkarniThis edited book provides a platform to discuss the state-of-the-art developments associated with traditional and advanced single-/multi-objective criteria optimization methods for addressing problems of performance enhancement of the products and systems design. The book in detail discusses the core ideas, underlying principles, mathematical formulations, critical reviews and experimentations, and solutions to complex problems from within the domains such as mechanical engineering design and manufacturing, fault detection and diagnosis, control systems, financial systems, machine learning in medical image processing as well as problems from operations research domain. It will serve as a valuable reference to academicians and industry practitioners involved in improving the efficiency, cost, performance, and durability of the products and systems. The chapters in this book may further give impetus to explore new avenues leading towards multidisciplinary research discussions associated with the resilience and sustainability of the existing systems.
Optimization Methods for Structural Engineering (Engineering Optimization: Methods and Applications)
by Ishaan R. Kale Ali SadollahThis contributed book focuses on optimization methods inspired by nature such as Harmony Search Algorithm, Drosophila Food-Search Algorithm, Cohort intelligence algorithm and its variations, fuzzy logic along with their hybridization variants. It also focuses on multi-objective optimization algorithms such as Non-Dominated Sorting Genetic Algorithm, Particle Swarm Optimization, Evolutionary Algorithm, Pareto Envelope Selection Algorithm, and Strength Pareto Evolutionary Algorithm. The content focuses on topics such as the optimal design of truss systems with various applications, the design and simulation of quarter car systems for comfort design, the road handling design and a balanced system, and topology optimization of 2-dimensional and 3-dimensional structure in linear elasticity, plasticity and fracture mechanics among others. This book is a useful reference for those in academia and industry.
Optimization Methods for User Admissions and Radio Resource Allocation for Multicasting over High Altitude Platforms
by Ahmed Ibrahim Attahiru AlfaThis book focuses on the issue of optimizing radio resource allocation (RRA) and user admission control (AC) for multiple multicasting sessions on a single high altitude platform (HAP) with multiple antennas on-board. HAPs are quasi-stationary aerial platforms that carry a wireless communications payload to provide wireless communications and broadband services. They are meant to be located in the stratosphere layer of the atmosphere at altitudes in the range 17-22 km and have the ability to fly on demand to temporarily or permanently serve regions with unavailable telecommunications infrastructure. An important requirement that the book focusses on is the development of an efficient and effective method for resource allocation and user admissions for HAPs, especially when it comes to multicasting. Power, frequency, space (antennas selection) and time (scheduling) are the resources considered in the problem over an orthogonal frequency division multiple access (OFDMA) HAP system.Due to the strong dependence of the total number of users that could join different multicast groups, on the possible ways we may allocate resources to these groups, it is of significant importance to consider a joint user to session assignments and RRA across the groups. From the service provider's point of view, it would be in its best interest to be able to admit as many higher priority users as possible, while satisfying their quality of service requirements. High priority users could be users subscribed in and paying higher for a service plan that gives them preference of admittance to receive more multicast transmissions, compared to those paying for a lower service plan. Also, the user who tries to join multiple multicast groups (i.e. receive more than one multicast transmission), would have preferences for which one he would favor to receive if resources are not enough to satisfy the QoS requirements.Technical topics discussed in the book include: • Overview on High Altitude Platforms, their different types and the recent works in this area Radio Resource Allocation and User Admission Control in HAPs Multicasting in a Single HAP System: System Model and Mathematical Formulation Optimization schemes that are designed to enhance the performance of a branch and bound technique by taking into account special mathematical structure in the problem formulation
Optimization Methods in Engineering: Select Proceedings of CPIE 2019 (Lecture Notes on Multidisciplinary Industrial Engineering)
by Mohit Tyagi Anish Sachdeva Vishal SharmaThis book comprises peer-reviewed contributions from the International Conference on Production and Industrial Engineering (CPIE) 2019. This volume provides insights into the current scenario and advances in the domain of industrial and production engineering in the context of optimum value. Optimization and its applicability in various areas of production and industrial engineering like selection of designing parameters and machining parameters, decisions related to conditions of optimum process/operation parameters, behavior of response variables, facilities planning and management, transportation and supply chain management, quality engineering, reliability and maintenance, product design and development, human factors and ergonomics, service system and service management, waste management, sustainable manufacturing and operations, systems design, and performance measurement are discussed in the book. Given the range of topics covered, this book can be useful for students, researchers, and professionals interested in latest optimization techniques related to industrial and production engineering.
Optimization Modelling Using R (Chapman & Hall/CRC Series in Operations Research)
by Timothy R. AndersonThis book covers using R for doing optimization, a key area of operations research, which has been applied to virtually every industry. The focus is on linear and mixed integer optimization. It uses an algebraic modeling approach for creating formulations that pairs naturally with an algebraic implementation in R. With the rapid rise of interest in data analytics, a data analytics platform is key. Working technology and business professionals need an awareness of the tools and language of data analysis. R reduces the barrier to entry for people to start using data analytics tools. Philosophically, the book emphasizes creating formulations before going intoimplementation. Algebraic representation allows for clear understanding and generalizationof large applications, and writing formulations is necessary to explain and convey the modeling decisions made. Appendix A introduces R. Mathematics is used at the level of subscripts and summations Refreshers are provided in Appendix B. This book: • Provides and explains code so examples are relatively clear and self-contained.• Emphasizes creating algebraic formulations before implementing.• Focuses on application rather than algorithmic details.• Embodies the philosophy of reproducible research.• Uses open-source tools to ensure access to powerful optimization tools.• Promotes open-source: all materials are available on the author’s github repository.• Demonstrates common debugging practices with a troubleshooting emphasis specific to optimization modeling using R.• Provides code readers can adapt to their own applications.This book can be used for graduate and undergraduate courses for students without a background in optimization and with varying mathematical backgrounds.
Optimization Models in Steganography Using Metaheuristics (Intelligent Systems Reference Library #187)
by Ajith Abraham Anand J. Kulkarni Dipti Kapoor SarmahThis book explores the use of a socio-inspired optimization algorithm (the Cohort Intelligence algorithm), along with Cognitive Computing and a Multi-Random Start Local Search optimization algorithm. One of the most important types of media used for steganography is the JPEG image. Considering four important aspects of steganography techniques – picture quality, high data-hiding capacity, secret text security and computational time – the book provides extensive information on four novel image-based steganography approaches that employ JPEG compression. Academics, scientists and engineers engaged in research, development and application of steganography techniques, optimization and data analytics will find the book’s comprehensive coverage an invaluable resource.
Optimization of Automated Software Testing Using Meta-Heuristic Techniques (EAI/Springer Innovations in Communication and Computing)
by Manju Khari Deepti Bala Mishra Biswaranjan Acharya Ruben Gonzalez CrespoThis book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing.Supports the advancement in the artificial intelligence used in software development;Advances knowledge on artificial intelligence based metaheuristic approach in software testing;Encourages innovation in traditional software testing field using recent artificial intelligence.·
Optimization of Chemical Processes: A Sustainable Perspective
by José María Ponce-Ortega Rogelio Ochoa-Barragán César Ramírez-MárquezThis textbook introduces readers to a comprehensive framework for the application of deterministic optimization strategies in the field of chemical processes, with a strong emphasis on sustainability.The book establishes a vital connection between fundamental deterministic optimization principles, optimization tools, and real-world application instances, all within the context of environmentally responsible practices. The approach put forth in this book is exceptionally versatile, allowing for the use of many optimization software and deterministic techniques.Contained in the book are many fundamental optimization concepts, encompassing linear programming, nonlinear programming, integer programming, and multi-objective optimization, all tailored to promote sustainable decision-making. Furthermore, the book provides practical examples illustrating the application of these techniques within sustainable chemical processes as tutorials.The textbook also explores the utilization of popular optimization software platforms such as GAMS, MATLAB, and Python, demonstrating how these tools can be leveraged for eco-friendly process optimization. Through this comprehensive framework, readers can not only acquire the skills needed to optimize a wide range of processes but also learn how to do so with sustainability at the forefront of their considerations. This approach streamlines the optimization process, eliminating unnecessary complications along the way and ensuring that environmental and ethical considerations are integral to the decision-making process.
Optimization of Complex Systems: Theory, Models, Algorithms and Applications (Advances in Intelligent Systems and Computing #991)
by Hoai An Le Thi Hoai Minh Le Tao Pham DinhThis 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.
Optimization of Computer Networks: A Hands-On Approach
by Pablo Pavón MariñoThis book covers the design and optimization of computer networks applying a rigorous optimization methodology, applicable to any network technology. It is organized into two parts. In Part 1 the reader will learn how to model network problems appearing in computer networks as optimization programs, and use optimization theory to give insights on them. Four problem types are addressed systematically - traffic routing, capacity dimensioning, congestion control and topology design. Part 2 targets the design of algorithms that solve network problems like the ones modeled in Part 1. Two main approaches are addressed - gradient-like algorithms inspiring distributed network protocols that dynamically adapt to the network, or cross-layer schemes that coordinate the cooperation among protocols; and those focusing on the design of heuristic algorithms for long term static network design and planning problems. Following a hands-on approach, the reader will have access to a large set of examples in real-life technologies like IP, wireless and optical networks. Implementations of models and algorithms will be available in the open-source Net2Plan tool from which the user will be able to see how the lessons learned take real form in algorithms, and reuse or execute them to obtain numerical solutions. An accompanying link to the author's own Net2plan software enables readers to produce numerical solutions to a multitude of real-life problems in computer networks (www.net2plan.com).
Optimization of Process Flowsheets through Metaheuristic Techniques
by Luis Germán Hernández-Pérez José María Ponce-OrtegaThis textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus®, HYSIS®, Super Pro Designer® linked to a variety of metaheuristic techniques implemented in Matlab®, Excel®, C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process. Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab® routines are included as electronic supporting material.
Optimization of Regional Industrial Structures and Applications (Systems Evaluation, Prediction, and Decision-Making)
by Yaoguo Dang Sifeng Liu Yuhong WangBased on research projects supported by the National Natural Science Foundation of China and Nanjing University of Aeronautics and Astronautics, Optimization of Regional Industrial Structures and Applications provides an authoritative introduction to and survey of the cutting-edge research and applications in industrial structure optimization. Empl
Optimization of Spiking Neural Networks for Radar Applications
by Muhammad ArsalanThis book offers a comprehensive exploration of the transformative role that edge devices play in advancing Internet of Things (IoT) applications. By providing real-time processing, reduced latency, increased efficiency, improved security, and scalability, edge devices are at the forefront of enabling IoT growth and success. As the adoption of AI on the edge continues to surge, the demand for real-time data processing is escalating, driving innovation in AI and fostering the development of cutting-edge applications and use cases. Delving into the intricacies of traditional deep neural network (deepNet) approaches, the book addresses concerns about their energy efficiency during inference, particularly for edge devices. The energy consumption of deepNets, largely attributed to Multiply-accumulate (MAC) operations between layers, is scrutinized. Researchers are actively working on reducing energy consumption through strategies such as tiny networks, pruning approaches, and weight quantization. Additionally, the book sheds light on the challenges posed by the physical size of AI accelerators for edge devices. The central focus of the book is an in-depth examination of SNNs' capabilities in radar data processing, featuring the development of optimized algorithms.
Optimization of Sustainable Enzymes Production: Artificial Intelligence and Machine Learning Techniques
by J. Satya Eswari Nisha SuryawanshiThis book is designed as a reference book and presents a systematic approach to analyze evolutionary and nature-inspired population-based search algorithms. Beginning with an introduction to optimization methods and algorithms and various enzymes, the book then moves on to provide a unified framework of process optimization for enzymes with various algorithms. The book presents current research on various applications of machine learning and discusses optimization techniques to solve real-life problems. •The book compiles the different machine learning models for optimization of process parameters for production of industrially important enzymes. The production and optimization of various enzymes produced by different microorganisms are elaborated in the book. •It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. •Covers the best-performing methods and approaches for optimization sustainable enzymes production with AI integration in a real-time environment. •Featuring valuable insights, the book helps readers explore new avenues leading towards multidisciplinary research discussions. The book is aimed primarily at advanced undergraduates and graduates studying machine learning, data science and industrial biotechnology. Researchers and professionals will also find this book useful.