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The book is a comprehensive collection of extended contributions from the Workshops on Computational Optimization 2022. Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real world and industrial problems arising in engineering, economics, medicine, and other domains can be formulated as optimization tasks. This book presents recent advances in computational optimization. The book includes important real problems like modeling of physical processes, parameter settings for controlling different processes, agricultural modeling transportation problems, energy management, machine scheduling, air pollution modeling, optimization of fast-food restaurant chain, and solving engineering and financial problems. It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming Monte Carlo method, and others. This book demonstrates how some real-world problems arising in engineering, economics, and other domains can be formulated as optimization problems.

This book constitutes the refereed proceedings of the 24th International Conference on Runtime Verification, RV 2024, held in Istanbul, Turkey, during October 15-17, 2024. The 11 full papers, 5 short papers and 2 tool papers included in this book were carefully reviewed and selected from 31 submissions. They were organized in topical sections as follows: Invited Paper; Cyber-physical Systems; Temporal Logics; Speci cation and Visualization; Deep Neural Networks; and Distributed Systems.

This book constitutes the refereed proceedings of CVM 2024, the 12th International Conference on Computational Visual Media, held in Wellington, New Zealand, in April 2024.The 34 full papers were carefully reviewed and selected from 212 submissions. The papers are organized in topical sections as follows:Part I: Reconstruction and Modelling, Point Cloud, Rendering and Animation, User Interations.Part II: Facial Images, Image Generation and Enhancement, Image Understanding, Stylization, Vision Meets Graphics.

​This book constitutes the refereed proceedings of CVM 2024, the 12th International Conference on Computational Visual Media, held in Wellington, New Zealand, in April 2024.The 34 full papers were carefully reviewed and selected from 212 submissions. The papers are organized in topical sections as follows:Part I: Reconstruction and Modelling, Point Cloud, Rendering and Animation, User Interations.Part II: Facial Images, Image Generation and Enhancement, Image Understanding, Stylization, Vision Meets Graphics.

This book constitutes the refereed proceedings of the 31st International Symposium on String Processing and Information Retrieval, SPIRE 2024, held in Puerto Vallarta, Mexico, during September 23–25, 2024. The 22 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 41 submissions. The papers reflect the continuation of the long and well-established tradition of encouraging high-quality research at the broad nexus of string processing, information retrieval, and computational biology.

This book constitutes the proceedings of the 18th Annual Conference on Theory and Applications of Models of Computation, TAMC 2024, which was held in Hong Kong, China, during May 13–15, 2024. The 30 full papers presented in this book were carefully reviewed and selected from 69 submissions. The main themes of the selected papers are computability, complexity, algorithms, information theory, as well as their integration with machine learning theory and the foundations of artificial intelligence.

This volume LNCS constitutes the refereed proceedings of 31st European MPI Users'Group Meeting, EuroMPI 2024, held in Perth, WA, Australia, during September 25-27, 2024. The 8 full papers presented here were carefully reviewed and selected from 19 submissions. These papers have been categorized under the following topical sections: Compile-time Correctness checks and optimization; Limitations and Extensions for GPGPUs in MPI; Improvements for MPI and MPI Ecosystem.

This book constitutes the proceedings of the 28th International Conference on Implementation and Application of Automata, CIAA 2024, held in Akita, Japan, during September 3-6, 2024. The 24 full papers and one invited paper presented here were carefully reviewed and selected from 38 submissions. These papers have been covering various fields in the application, implementation, and theory of automata and related structures.

This book constitutes the refereed proceedings of the 20th Conference on Computabilitty in Europe, CiE 2024, held in Amsterdam, The Netherlands, during July 8–12, 2024 The 26 full papers and 2 short papers included in this book were carefully reviewed and selected from 43 submissions. This CIE 2024 focus on development of computability-related science, ranging over mathematics, computer science and applications in various natural and engineering sciences.

This book provides an insight into 12th International Conference on Soft Computing for Problem Solving (SocProS 2023), organized by The Department of Applied Mathematics and Scientific Computing, Saharanpur Campus of Indian Institute of Technology, Roorkee, India, in conjunction with Continuing Education Center during 11–13 August 2023. This book presents the latest achievements and innovations in the interdisciplinary areas of soft computing, machine learning, and data science. It covers original research papers in the areas of algorithms (artificial neural network, deep learning, statistical methods, genetic algorithm, and particle swarm optimization) and applications (data mining and clustering, computer vision, medical and health care, finance, data envelopment analysis, business, and forecasting applications). This book is beneficial for young as well as experienced researchers dealing across complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.

This book provides an insight into 12th International Conference on Soft Computing for Problem Solving (SocProS 2023), organized by The Department of Applied Mathematics and Scientific Computing, Saharanpur Campus of Indian Institute of Technology, Roorkee, India, in conjunction with Continuing Education Center during 11–13 August 2023. This book presents the latest achievements and innovations in the interdisciplinary areas of soft computing, machine learning, and data science. It covers original research papers in the areas of algorithms (artificial neural network, deep learning, statistical methods, genetic algorithm, and particle swarm optimization) and applications (data mining and clustering, computer vision, medical and health care, finance, data envelopment analysis, business, and forecasting applications). This book is beneficial for young as well as experienced researchers dealing across complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.

Based on the shared journey of two researchers, this book explores enhancing algorithms for the resource-constrained project scheduling problem. It examines the search for and significance of project data from multiple, distinct perspectives. In the first part, the quest for project data is presented as a continuous exploration of the complexity of the resource-constrained project scheduling problem. This quest is pursued by solving this challenging problem with the aid of state-of-the-art algorithms from the literature, each time gaining a deeper understanding of its challenging nature. To provide insights into the problem's complexity, project data is created, manipulated, and analyzed in depth to make current projects easier or harder to schedule. This challenging quest for project data has resulted in new project databases for academic research, new ways of testing future algorithms, and insights into how to improve future algorithms to solve this project scheduling problem with limited resources. In turn, the second part discusses the relevance of project data, demonstrating to the reader the importance of the academic research presented in the first part for the professional world. It shows how project data can be used to calibrate real project data, leading to improved decision-making, e.g. for project scheduling, forecasting, and risk analysis. The book extends a warm invitation to academics and practitioners alike, as fellow seekers of knowledge, to enhance their project management skills.

Dezentrale Autonome Organisationen (DAOs) sind ein neues Organisationsmodell, das auf der algorithmischen Festschreibung von Regeln in einem blockchainbasierten Softwareprogramm basiert. Ihr Versprechen: Eine alternative Art und Weise des Organisierens zu ermöglichen, die sich durch nichthierarchische („dezentrale“) Zusammenarbeit und umfassende technologische Koordination auszeichnet. Als Musterbeispiel der „Governance durch Algorithmen“ verdeutlichen DAOs, dass in der digitalisierten Gesellschaft immer häufiger Konstellationen auftreten, in denen algorithmische und menschliche Handlungsmacht aufeinandertreffen. In dem vorliegenden Buch wird vor diesem Hintergrund untersucht, wie algorithmische Governance der eingesetzten Softwareprogramme und die Autonomie menschlicher Handelnder in der Organisationspraxis von DAOs zusammenwirken. Zur Beantwortung dieser Frage werden empirische Fallstudien in drei DAO-Softwareprojekten durchgeführt. Die Auswertung ergibt, dass beide ein Spannungsverhältnis konstituieren: So stehen die Mitglieder der Projekte in zahlreichen Situationen des Projektalltags vor der Herausforderung, die algorithmisch festgelegten Regeln und Ressourcen mit menschlichen Strukturierungsleistungen zu vereinen.

This book provides a foundation in stochastic, linear, and mixed-integer programming algorithms with a focus on practical computer algorithm implementation. The purpose of this book is to provide a foundational and thorough treatment of the subject with a focus on models and algorithms and their computer implementation. The book's most important features include a focus on both risk-neutral and risk-averse models, a variety of real-life example applications of stochastic programming, decomposition algorithms, detailed illustrative numerical examples of the models and algorithms, and an emphasis on computational experimentation. With a focus on both theory and implementation of the models and algorithms for solving practical optimization problems, this monograph is suitable for readers with fundamental knowledge of linear programming, elementary analysis, probability and statistics, and some computer programming background. Several examples of stochastic programming applications areincluded, providing numerical examples to illustrate the models and algorithms for both stochastic linear and mixed-integer programming, and showing the reader how to implement the models and algorithms using computer software.

Written by an experienced operations research practitioner with a strong applied mathematics background, this book offers practical insights into how to approach optimization problems, how to develop intelligent and efficient mathematical models and algorithms, and how to implement and deliver software products to customers. With a focus on revealing the similarities and differences between academia and industry in mathematical modeling, the book provides useful tips and advice based on the author's extensive experience as a principal developer working to solve real-world optimization problems for several major high-tech companies.The book offers valuable food for thought for researchers and practical guidance for graduate students preparing for their future projects in the industry. It is also an essential resource for practitioners working in the industrial, business, and service sectors.

This book provides a comprehensive review of the latest developments in optimization based learning algorithms within the field of electrical engineering. It covers various power system applications including efficient power system operation, load forecasting, fault analysis, home automation and efficient smart grid management. Each application is accompanied by case studies and a literature review in self-contained chapters. The book is dedicated to study the effectiveness of intelligent methods in addressing the power system problems and its mitigation using optimization algorithms. It discusses several optimization algorithms such as random forest algorithm, metaheuristic algorithm, scaled conjugate gradient descent algorithm, artificial bee colony algorithm etc. and their usability in intelligent decision makers for the various optimization problems in electrical engineering. This timely book serves as a practical guide and reference sources for students, researchers and professionals.

This book presents algorithms and tools that are designed to model and extract information from personal contact networks, which represent which individuals in a population are physically in contact with one another. The authors developed these tools based on research they conducted during the COVID-19 pandemic, with the goal of improving responses to epidemics in the future. The book provides methods for modelling the transmission of infection across a population. The authors explain how an epidemic model can be used to strategically distribute vaccines and minimize the spread of a virus. The book shows how evolutionary computation, graph compression, and network induction can be utilized to manage issues that arise from an epidemic.

This textbook offers an introduction to topics in algorithms and programming with python. It is originally intended for mathematical students not sufficiently aware about these computer science fields seeking a deeper understanding. It addresses fundamental questions on how to analyze the performance of an algorithm and equips readers with the skills to implement them using python. The textbook is organized in two parts. Part I introduces Python Programming offering a solid foundation to python essentials. Topics covered include first steps in python programming, programs, functions and recursion, data structures. Part II shifts focus to Algorithms and covers topics such as algorithm performance, recursion, the sorting problem, trees as data structures, etc. This book has its origins from several different courses given in the context of thematic schools to diverse audiences in different countries over the years. These countries include Cambodia, Kenya, and Madagascar.

This book covers the basics of numerical methods. Avoiding the definition-theorem-proof style, it instead focuses on numerical examples and simple pseudo-codes. The text begins with a chapter on floating point arithmetic before moving on to discuss norms, conditions numbers, solutions of systems of equations, the least squares problem, eigenvalue problems, interpolation, numerical integration, ordinary differential equations, optimization (including a detailed case study), and practical error estimations. Exercises (partly in MATLAB) are provided at the end of each chapter. Suitable for readers with minimal mathematical knowledge, the book not only offers an elementary introduction to numerical mathematics for programmers and engineers but also provides supporting material for students and teachers of mathematics.

This textbook features new material on advanced topics, such as calculating Fourier transforms, finding minimum cost flows in graphs, and using automata in string problems. Critically, the text accessibly describes and shows how competitive programming is a proven method of implementing and testing algorithms, as well as developing computational thinking and improving both programming and debugging skills. Topics and features: Introduces dynamic programming and other fundamental algorithm design techniques, and investigates a wide selection of graph algorithms Compatible with the IOI Syllabus, yet also covering more advanced topics, such as maximum flows, Nim theory, and suffix structures Provides advice for students aiming for the IOI contest Surveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programming Examines the use of the Python language in competitive programming Discusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard library Explores how GenAI will impact on the future of the field Covers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queries Describes a selection of more advanced topics, including square-root algorithms and dynamic programming optimization Fully updated, expanded and easy to follow, this core textbook/guide is an ideal reference for all students needing to learn algorithms and to practice for programming contests. Knowledge of programming basics is assumed, but previous background in algorithm design or programming contests is not necessary. With its breadth of topics, examples and references, the book is eminently suitable for both beginners and more experienced readers alike.

This book explains how all persons with Western European ancestry are related through a Unifying Ancestry. The author presents the knowledge metrics needed to derive the best representation for a Unifying Ancestry. The book uses example lineages to historically notable persons including relationships to U.S. Presidents, royal families, actors, and singers in order to demonstrate these points. This third edition is based upon expanded data, applying the algorithms to validate the Unifying Ancestry to a 348,844-person Research Genealogy. The author successfully demonstrates that a Unifying Ancestry with 38,533 persons is sufficient to identify familial relationships between Western Europeans.

This book gathers a collection of selected works and new research results of scholars and graduate students presented at International Conference on Evolutionary Artificial Intelligence (ICEAI 2023) held in Malaysia during 13-14 September 2023. The focus of the book is interdisciplinary in nature and includes research on all aspects of evolutionary computation to find effective solutions to a wide range of computationally difficult problems. The book covers topics such as particle swarm optimization, evolutionary programming, genetic programming, hybrid evolutionary algorithms, ant colony optimization, evolutionary neural networks, evolutionary reinforcement learning, genetic algorithms, memetic algorithms, novel bio-inspired algorithms, evolving multi-agent systems, agent-based evolutionary approaches, and evolutionary game theory.

This book reviews recent advances in theory and applications of genetic algorithm (GA). The book is composed of five parts; Part 1 of the book involves the chapters about the advances in GA theory. Part 2 concerns applications in health, society, and economy. Part 3 has an inclusive focus on application in power systems, and Part 4 concerns the applications of GA in electrical vehicle industries. Finally, Part 5 includes applications in signal and image processing.

La eficiencia y la optimización se erigen como principios clave de la ingeniería y la gestión. Poseer las herramientas y técnicas de optimización correctas se ha vuelto indispensable. La revolución tecnológica y el auge del análisis de datos han resaltado el inmenso valor de los algoritmos de optimización, capaces de descubrir las mejores soluciones en una amplia gama de escenarios, desde la optimización de recursos en proyectos de ingeniería hasta la estrategia de toma de decisiones en la gestión empresarial. Sin embargo, adentrarse en el aprendizaje de la optimización numérica representa un reto significativo, que demanda una sólida comprensión de las matemáticas y la programación informática. La abrumadora cantidad de nueva información y la jerga especializada pueden ser particularmente intimidantes sin la guía de un experto. Este libro se presenta como la solución a este desafío: ofrece una introducción al fascinante mundo de la optimización numérica con un estilo claro y ameno, proporcionando simultáneamente las herramientas esenciales de matemáticas y programación de manera secuencial y accesible, sin necesidad de conocimientos previos especializados. Se distingue de otras publicaciones especializadas por su enfoque eminentemente práctico. Incluye ejemplos en MATLAB, que sirven como herramienta práctica para reducir la distancia entre la teoría y su aplicación en el mundo real. La inclusión de ejemplos de código ya preparados y su explicación línea por línea no solo hace que la materia resulte más atractiva, sino que también anima a experimentar, modificar y mejorar el código con sus propias ideas. Si se acerca a la optimización numérica por primera vez como estudiante, este libro será un recurso de gran valor para sus estudios, y le brindará un entendimiento profundo de los algoritmos de optimización y su aplicación práctica. Si es un profesional que busca adentrarse en el campo de la optimización sin ser un especialista, encontrará en este libro un excelente punto de partida.

The book explains basic ideas behind several kinds of applied multi-objective optimization and shows how it will be applied in practical contexts in the domain of healthcare, engineering design, and manufacturing. The book discusses how meta-heuristic algorithms are successful in resolving challenging, multi-objective optimization issues in various disciplines, including engineering, economics, medical and environmental management. The topic is useful for graduates, researchers and lecturers in optimization, engineering, management science and computer science.

This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms—supported by motivating examples—that bring meaning to the problems faced by computer programmers. The idea of computational complexity is introduced, demonstrating what can and cannot be computed efficiently at scale, helping programmers make informed judgements about the algorithms they use. The easy-to-read text assumes some basic experience in computer programming and familiarity in an object-oriented language, but not necessarily with Python.Topics and features:Includes introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective coursesProvides learning goals, review questions, and programming exercises in each chapter, as well as numerous examplesPresents a primer on Python for those coming from a different language backgroundAdds a new chapter on multiprocessing with Python using the DragonHPC multinode implementation of multiprocessing (includes a tutorial)Reviews the use of hashing in sets and maps, and examines binary search trees, tree traversals, and select graph algorithmsOffers downloadable programs and supplementary files at an associated website to help studentsStudents of computer science will find this clear and concise textbook invaluable for undergraduate courses on data structures and algorithms, at both introductory and advanced levels. The book is also suitable as a refresher guide for computer programmers starting new jobs working with Python.Dr. Kent D. Lee is a Professor Emeritus of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer books, Python Programming Fundamentals, and Foundations of Programming Languages.Dr. Steve Hubbard is a Professor Emeritus of Mathematics and Computer Science at Luther College.

This book reports the developments of the Total Least Square (TLS) algorithms for parameter estimation and adaptive filtering. Specifically, it introduces the authors'latest achievements in the past 20 years, including the recursive TLS algorithms, the approximate inverse power iteration TLS algorithm, the neural based MCA algorithm, the neural based SVD algorithm, the neural based TLS algorithm, the TLS algorithms under non-Gaussian noises, performance analysis methods of TLS algorithms, etc. In order to faster the understanding and mastering of the new methods provided in this book for readers, before presenting each new method in each chapter, a specialized section is provided to review the closely related several basis models. Throughout the book, large of procedure of new methods are provided, and all new algorithms or methods proposed by us are tested and verified by numerical simulations or actual engineering applications. Readers will find illustrative demonstration examples on a range of industrial processes to study. Readers will find out the present deficiency and recent developments of the TLS parameter estimation fields, and learn from the the authors'latest achievements or new methods around the practical industrial needs. In my opinion, this book can be assimilated by advanced undergraduates and graduate students, as well as statisticians, because of the new tools in data analysis, applied mathematics experts, because of the novel theories and techniques that we propose, engineers, above all for the applications in control, system identification, computer vision, and signal processing.

Here is your in-depth guide to cryptography and cryptanalysis in Java. This book includes challenging cryptographic solutions that are implemented in Java 21 and Jakarta EE 11. It provides a robust introduction to Java 21's new features and updates, a roadmap for Jakarta EE 11 security mechanisms, a unique presentation of the'hot points'(advantages and disadvantages) from the Java Cryptography Architecture (JCA), a new chapter on Quantum cryptography, and more. The book dives into the classical simple cryptosystems that form the basis of modern cryptography, with fully working solutions (encryption/decryption operations). Pseudo-random generators are discussed as well as real-life implementations. Hash functions are covered along with practical cryptanalysis methods and attacks, asymmetric and symmetric encryption systems, signature and identification schemes. The book wraps up with a presentation of lattice-based cryptography and the NTRU framework library. Modern encryption schemes for cloud and big data environments (homomorphic encryption and searchable encryption) also are included. After reading and using this book, you will be proficient with crypto algorithms and know how to apply them to problems you may encounter. New to This Edition: The modernized Second Edition is updated to reflect the latest language features in Java 21 and Jakarta 11, along with the introduction of a new chapter on Quantum Cryptography (Chapter 6). What You Will Learn Develop programming skills for writing cryptography algorithms in Java Dive into security schemes and modules using Java Explore “good” vs “bad” cryptography based on processing execution times and reliability Play with pseudo-random generators, hash functions, etc. Leverage lattice-based cryptography methods, the NTRU framework library, and more Who This Book Is For Those who want to learn and leverage cryptography and cryptanalysis using Java. Some prior Java and/or algorithm programming exposure is highly recommended.

This text focuses on simple and easy-to-use design strategies for solving complex engineering problems that arise in several fields of engineering design, namely non-convex optimization problems. The main optimization tool used in this book to tackle the problem of nonconvexity is the Heuristic Kalman Algorithm (HKA). The main characteristic of HKA is the use of a stochastic search mechanism to solve a given optimization problem. From a computational point of view, the use of a stochastic search procedure appears essential for dealing with non-convex problems.The topics discussed in this monograph include basic definitions and concepts from the classical optimization theory, the notion of the acceptable solution, machine learning, the concept of preventive maintenance, and more. The Heuristic Kalman Algorithm discussed in this book applies to many fields such as robust structured control, electrical engineering, mechanical engineering, machine learning, reliability, and preference models. This large coverage of practical optimization problems makes this text very useful to those working on and researching systems design. The intended audience includes industrial engineers, postgraduates, and final-year undergraduates in various fields of systems design.