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Optimisation in Signal and Image Processing (Wiley-iste Ser.)
by Patrick SiarryThis book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms, and artificial immune systems).
Optimisation of Dynamic Heterogeneous Rainfall Sensor Networks in the Context of Citizen Observatories (IHE Delft PhD Thesis Series)
by Juan Carlos Chacon-HurtadoPrecipitation drives the dynamics of flows and storages in water systems, making its monitoring essential for water management. Conventionally, precipitation is monitored using in-situ and remote sensors. In-situ sensors are arranged in networks, which are usually sparse, providing continuous observations for long periods at fixed points in space, and due to the high costs of such networks, they are often sub-optimal. To increase the efficiency of the monitoring networks, we explore the use of sensors that can relocate as rainfall events develop (dynamic sensors), as well as increasing the number of sensors involving volunteers (citizens). This research focusses on the development of an approach for merging heterogeneous observations in non-stationary precipitation fields, exploring the interactions between different definitions of optimality for the design of sensor networks, as well as development of algorithms for the optimal scheduling of dynamic sensors. This study was carried out in three different case studies, including Bacchiglione River (Italy), Don River (U.K.) and Brue Catchment (U.K.) The results of this study indicate that optimal use of dynamic sensors may be useful for monitoring precipitation to support water management and flow forecasting.
Optimisation of Manufacturing Processes: A Response Surface Approach
by Mark EvansMany engineering companies around the world are currently undergoing a quality control and improvement revolution that originally started in Japan many decades ago and this book provides a brief overview of this revolution. Robust design is a central component of the modern approach to quality improvement and is a phrase used to describe any engineering activity whose objective is to develop high quality products (and processes) at low cost. A key characteristic of robust design is the use of statistically planned (designed) experiments to identify those process variables that determine product quality. Robust design was developed in Japan by G. Taguchi in the early 1950s and its widespread use throughout Japanese industry is one of the main reasons why the country has emerged as a major producer of relatively cheap high quality products, especially in the automobile, home electronics and microprocessing sectors. Despite its early success in Japan, robust design remained virtually untried in the United States and Europe until the early 1980s. However, the realisation that quality is a vital ingredient required for success in today's highly global and competitive markets has since prompted Western companies to embrace the robust design concept. This book explores the planning, implementation and analysis of experiments designed both to improve existing manufacturing process and to create newer and better processes and products.
Optimisation of Robotic Disassembly for Remanufacturing (Springer Series in Advanced Manufacturing)
by Yuanjun Laili Yongjing Wang Yilin Fang Duc Truong PhamThis book illustrates the main characteristics, challenges and optimisation requirements of robotic disassembly. It provides a comprehensive insight on two crucial optimisation problems in the areas of robotic disassembly through a group of unified mathematical models. The online and offline optimisation of the operational sequence to dismantle a product, for example, is represented with a list of conflicting objectives and constraints. It allows the decision maker and the robots to match the situation automatically and efficiently. To identify a generic solution under different circumstances, classical metaheuristics that can be used for the optimisation of robotic disassembly are introduced in detail. A flexible framework is then presented to implement existing metaheuristics for sequence planning and line balancing in the circumstance of robotic disassembly. Optimisation of Robotic Disassembly for Remanufacturing provides practical case studies on typical product instances to help practitioners design efficient robotic disassembly with minimal manual operation, and offers comparisons of the state-of-the-art metaheuristics on solving the key optimisation problems. Therefore, it will be of interest to engineers, researchers, and postgraduate students in the area of remanufacturing.
Optimised Projections for the Ab Initio Simulation of Large and Strongly Correlated Systems
by David D. O'ReganDensity functional theory (DFT) has become the standard workhorse for quantum mechanical simulations as it offers a good compromise between accuracy and computational cost. However, there are many important systems for which DFT performs very poorly, most notably strongly-correlated materials, resulting in a significant recent growth in interest in 'beyond DFT' methods. The widely used DFT+U technique, in particular, involves the addition of explicit Coulomb repulsion terms to reproduce the physics of spatially-localised electronic subspaces. The magnitude of these corrective terms, measured by the famous Hubbard U parameter, has received much attention but less so for the projections used to delineate these subspaces. The dependence on the choice of these projections is studied in detail here and a method to overcome this ambiguity in DFT+U, by self-consistently determining the projections, is introduced. The author shows how nonorthogonal representations for electronic states may be used to construct these projections and, furthermore, how DFT+U may be implemented with a linearly increasing cost with respect to system size. The use of nonorthogonal functions in the context of electronic structure calculations is extensively discussed and clarified, with new interpretations and results, and, on this topic, this work may serve as a reference for future workers in the field.
Optimising and Digitising Supply Chain Processes
by Torsten BeckerProduction and logistics companies can achieve significant competitive advantage with their supply chain and production processes. This book provides managers, practitioners, consultants and students with a comprehensive understanding of process optimisation. It covers a wide range of tools, methods and tried-and-tested procedures for improving performance in these areas. The methodological toolbox from the various optimisation philosophies - Lean Production, Supply Chain, Six Sigma, Continuous Improvement Processes and Theory of Constraints - is presented and evaluated. Digital tools for process analysis, such as process mining, are described. Procedures and approaches are described for the individual steps of comprehensive process optimisation. These include process analysis methods such as ARIS, value stream mapping, the supply chain operations reference model (SCOR), and numerous process evaluation methods. One focus of the book is the presentation of pragmatic implementation approaches and procedures, including agile project management methods. Three project examples from the author's consulting practice are used to describe the results of complex changes. The book contains many hints and tips for extensive process improvements. The author has many years of industry experience and has been advising leading companies in various sectors for over 25 years. It presents end-to-end improvement approaches for systematically increasing supply chain and production performance. Using tried-and-tested tools and examples, the reader learns how to successfully handle supply chain projects from the initial idea to implementation. Based on the author's implementation experience, a set of methods covers all aspects of production and supply chain process optimisation. With the detailed procedures, the book offers recommendations on running supply chain projects efficiently and successfully and which tools effectively support the work in the individual project phases.
Optimising NMR Spectroscopy Through Method and Software Development (Springer Theses)
by Jonathan YongThis book provides a comprehensive overview of Nuclear Magnetic Resonance (NMR) theory, its applications, and advanced techniques to improve the quality and speed of NMR data acquisition. In this book, the author expands his outstanding Ph.D. thesis and provides a valuable resource for researchers, professionals, and students in the field of NMR spectroscopy. The book covers quantum mechanics basics, and topics like density operators, pulse sequences, 1D pulse acquisition, INEPT (Insensitive nuclei enhancement by polarization transfer), product operators, and 2D NMR principles. It also explores innovative experiments like States HSQC (Heteronuclear Single Quantum Coherence) and echo-antiecho HSQC with gradients. In the subsequent chapters, the author discusses Pure Shift NMR, including PSYCHE (Pure Shift Yielded by Chirp Excitation) and its optimizations, such as waveform parameterization and time-reversal methods. The 'Discrete PSYCHE' approach and Ultrafast PSYCHE-iDOSY (Diffusion-ordered spectroscopy) are also highlighted. This book presents the POISE (Parameter Optimisation by Iterative Spectral Evaluation) software for real-time NMR experiment optimization, including pulse width calibration and Ernst angle optimization, and demonstrates applications across various NMR experiments. Lastly, the book examines accelerated 2D NMR data collection and the NOAH (NMR by Ordered Acquisition using 1H detection) supersequences, emphasizing automated pulse program creation using GENESIS (GENEration of Supersequences In Silico). Covered NMR experiments include 13C sensitivity-enhanced HSQC, 15N HMQC (Heteronuclear Multiple Quantum Coherence), dual HSQC, HSQC-TOCSY (Total Correlation Spectroscopy), HMBC (Heteronuclear Multiple Bond Correlation), and ADEQUATE (Adequate Sensitivity Double-Quantum Spectroscopy).
The Optimist's Telescope: Thinking Ahead in a Reckless Age
by Bina VenkataramanA trailblazing exploration of how we can plan better for the future: our own, our families’, and our society’s. Instant gratification is the norm today—in our lives, our culture, our economy, and our politics. Many of us have forgotten (if we ever learned) how to make smart decisions for the long run. Whether it comes to our finances, our health, our communities, or our planet, it’s easy to avoid thinking ahead.The consequences of this immediacy are stark: Superbugs spawned by the overuse of antibiotics endanger our health. Companies that fail to invest stagnate and fall behind. Hurricanes and wildfires turn deadly for communities that could have taken more precaution. Today more than ever, all of us need to know how we can make better long-term decisions in our lives, businesses, and society. Bina Venkataraman sees the way forward. A former journalist and adviser in the Obama administration, she helped communities and businesses prepare for climate change, and she learned firsthand why people don’t think ahead—and what can be done to change that. In The Optimist’s Telescope, she draws from stories she has reported around the world and new research in biology, psychology, and economics to explain how we can make decisions that benefit us over time. With examples from ancient Pompeii to modern-day Fukushima, she dispels the myth that human nature is impossibly reckless and highlights the surprising practices each of us can adopt in our own lives—and the ones we must fight for as a society. The result is a book brimming with the ideas and insights all of us need in order to forge a better future.
Optimization: Algorithms and Applications
by Rajesh Kumar AroraChoose the Correct Solution Method for Your Optimization ProblemOptimization: Algorithms and Applications presents a variety of solution techniques for optimization problems, emphasizing concepts rather than rigorous mathematical details and proofs. The book covers both gradient and stochastic methods as solution techniques for unconstrained and co
Optimization: 100 Examples
by Simon SerovajskyOptimization: 100 Examples is a book devoted to the analysis of scenarios for which the use of well-known optimization methods encounter certain difficulties. Analysing such examples allows a deeper understanding of the features of these optimization methods, including the limits of their applicability. In this way, the book seeks to stimulate further development and understanding of the theory of optimal control. The study of the presented examples makes it possible to more effectively diagnose problems that arise in the practical solution of optimal control problems, and to find ways to overcome the difficulties that have arisen. Features Vast collection of examples Simple. accessible presentation Suitable as a research reference for anyone with an interest in optimization and optimal control theory, including mathematicians and engineers Examples differ in properties, i.e. each effect for each class of problems is illustrated by a unique example. Simon Serovajsky is a professor of mathematics at Al-Farabi Kazakh National University in Kazakhstan. He is the author of many books published in the area of optimization and optimal control theory, mathematical physics, mathematical modelling, philosophy and history of mathematics as well as a long list of high-quality publications in learned journals.
Optimization Aided Design: Reinforced Concrete
by Georgios Gaganelis Peter Mark Patrick FormanConcrete is the most used building material. Its main component, cement, however, accounts production- related for up to 10 % of global CO2 emissions and is therefore a major contributor to human-induced climate change. Due to its low tensile strength, concrete must be further enhanced in tension with adequate reinforcement, such as steel. Producing the latter therefore additionally impacts the environment. Consequently, reducing the material amount for design and construction of structures, thus lowering material- and transport-induced emissions, represents a key element to climate protection. In this context, meeting the essential requirements ? sustainability, serviceability, durability ? is yet indispensable. The book presents innovative optimization aided design methods for concrete structures. Mathematical optimization is applied to practical problems of structural concrete at each level: from external, through internal structure identification to cross-section design. It is shown how to design resource-efficient structures following the flux of forces, how to optimally adapt reinforcement layouts to the internal force flow, and how to efficiently cope with demanding cross-sectional design tasks such as biaxial bending. The optimization aided design methods are discussed in detail and described vividly. They are independent of standards, concrete material (normal to ultra-high performance) and reinforcement type (steel fibers to carbon bars), thus universally applicable. The book illustrates the different approaches with numerous figures and calculation examples. Existing applications in structural engineering are presented to demonstrate the potential of optimization aided design concepts, including ultra-lightweight hybrid beams, thin concrete solar collectors, and improved reinforcement layouts for tunnel lining segments.
Optimization and Applicability of Bioprocesses
by Vipin Chandra Kalia Hemant J. Purohit Atul N. Vaidya Anshuman A. KhardenavisThis book argues that the sustainable management of resources requires a systematic approach that primarily involves the integration of green innovative biotechnological strategies and eco-engineering. It discusses how microbial community intelligence can be used for waste management and bio-remediation and explains how biological processes can be optimized by integrating genomics tools to provide perspectives on sustainable development. The book describes the application of modern molecular techniques such as fluorescence in situ hybridization (FISH), highly sensitive catalyzed reporter deposition (CARD)-FISH, in situ DNA-hybridization chain reaction (HCR) and methods for detecting mRNA and/or functional genes to optimize bioprocessess. These techniques, supplemented with metagenomic analysis, reveal that a large proportion of micro-organisms still remain to be identified and also that they play a vital role in establishing bioprocesses.
Optimization and Business Improvement Studies in Upstream Oil and Gas Industry
by Sanjib ChowdhuryDelves into the core and functional areas in the upstream oil and gas industry covering a wide range of operations and processes Oil and gas exploration and production (E&P) activities are costly, risky and technology-intensive. With the rise in global demand for oil and fast depletion of easy reserves, the search for oil is directed to more difficult areas - deepwater, arctic region, hostile terrains; and future production is expected to come from increasingly difficult reserves - deeper horizon, low quality crude. All these are making E&P activities even more challenging in terms of operations, technology, cost and risk. Therefore, it is necessary to use scarce resources judiciously and optimize strategies, cost and capital, and improve business performance in all spheres of E&P business. Optimization and Business Improvement Studies in Upstream Oil and Gas Industry contains eleven real-life optimization and business improvement studies that delve into the core E&P activities and functional areas covering a wide range of operations and processes. It uses various quantitative and qualitative techniques, such as Linear Programing, Queuing theory, Critical Path Analysis, Economic analysis, Best Practices Benchmark, Business Process Simplification etc. to optimize Productivity of drilling operations Controllable rig time loss Deepwater exploration strategy Rig move time and activity schedule Offshore supply vessel fleet size Supply chain management system Strategic workforce and human resource productivity Base oil price for a country Standardize consumption of materials Develop uniform safety standards for offshore installations Improve organizational efficiency through business process simplification The book will be of immense interest to practicing managers, professionals and employees at all levels/ disciplines in oil and gas industry. It will also be useful to academicians, scholars, educational institutes, energy research institutes, and consultants dealing with oil and gas. The work can be used as a practical guide to upstream professionals and students in petroleum engineering programs.
Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making: Artificial Intelligence Applications (Intelligent Data-Driven Systems and Artificial Intelligence)
by Irfan Ali Umar Muhammad Modibbo Asaju La’aro Bolaji Harish GargThis book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0, and social responsibility.This book: Addresses solving practical problems such as supply chain management, take-off, and healthcare analytics using intelligent computing Presents a comparative analysis of machine learning algorithms for power consumption prediction Discusses a machine learning-based multi-objective optimization technique for load balancing in an integrated fog cloud environment Illustrates a data-driven optimization concept for modeling environmental and economic sustainability Explains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goals The text is primarily written for graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, mathematics and statistics, computer science and engineering.
Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making: Optimization Applications (Intelligent Data-Driven Systems and Artificial Intelligence)
by Irfan Ali Umar Muhammad Modibbo Asaju La’aro Bolaji Harish GargThis book comprehensively discusses nature‑inspired algorithms, deep learning methods, applications of mathematical programming, and artificial intelligence techniques. It further covers important topics such as the use of machine learning and the Internet of Things and multi‑objective optimization under Fermatean hesitant fuzzy and uncertain environment.This book: Addresses solving practical problems such as supply chain management, smart manufacturing, and healthcare analytics using intelligent computing and discusses solving the fuzzy inference system in ant colony optimization for traveling salesman problem Presents an overview of artificial intelligence (AI) and explainable AI decision‑making (XAIDM) and illustrates a data‑driven optimization concept for modeling environmental and economic sustainability Discusses machine learning‑based multi‑objective optimization technique for load balancing in integrated fog‑cloud environment Explains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goals Discusses sustainable transit of hazardous waste, green fractional transportation system, perishable inventory, M‑estimation of functional regression operator, and intuitionistic fuzzy sets applications The text is primarily written for graduate students and academic researchers in diverse fields, including operations research, mathematics, statistics, computer science, information and communication technology, and industrial engineering.
Optimization and Control Methods in Industrial Engineering and Construction
by Honglei Xu Xiangyu WangThis book presents recent advances in optimization and control methods with applications to industrial engineering and construction management. It consists of 15 chapters authored by recognized experts in a variety of fields including control and operation research, industrial engineering and project management. Topics include numerical methods in unconstrained optimization, robust optimal control problems, set splitting problems, optimum confidence interval analysis, a monitoring networks optimization survey, distributed fault detection, nonferrous industrial optimization approaches, neural networks in traffic flows, economic scheduling of CCHP systems, a project scheduling optimization survey, lean and agile construction project management, practical construction projects in Hong Kong, dynamic project management, production control in PC4P and target contracts optimization. The book offers a valuable reference work for scientists, engineers, researchers and practitioners in industrial engineering and construction management.
Optimization and Control of Bilinear Systems
by Panos M. Pardalos Vitaliy A. YatsenkoCovers developments in bilinear systems theory Focuses on the control of open physical processes functioning in a non-equilibrium mode Emphasis is on three primary disciplines: modern differential geometry, control of dynamical systems, and optimization theory Includes applications to the fields of quantum and molecular computing, control of physical processes, biophysics, superconducting magnetism, and physical information science
Optimization and Control of Dynamic Systems
by Henryk GóreckiThis book offers a comprehensive presentation of optimization and polyoptimization methods. The examples included are taken from various domains: mechanics, electrical engineering, economy, informatics, and automatic control, making the book especially attractive. With the motto “from general abstraction to practical examples,” it presents the theory and applications of optimization step by step, from the function of one variable and functions of many variables with constraints, to infinite dimensional problems (calculus of variations), a continuation of which are optimization methods of dynamical systems, that is, dynamic programming and the maximum principle, and finishing with polyoptimization methods. It includes numerous practical examples, e.g., optimization of hierarchical systems, optimization of time-delay systems, rocket stabilization modeled by balancing a stick on a finger, a simplified version of the journey to the moon, optimization of hybrid systems and of the electrical long transmission line, analytical determination of extremal errors in dynamical systems of the rth order, multicriteria optimization with safety margins (the skeleton method), and ending with a dynamic model of bicycle. The book is aimed at readers who wish to study modern optimization methods, from problem formulation and proofs to practical applications illustrated by inspiring concrete examples.
Optimization and Games for Controllable Markov Chains: Numerical Methods with Application to Finance and Engineering (Studies in Systems, Decision and Control #504)
by Julio B. Clempner Alexander PoznyakThis book considers a class of ergodic finite controllable Markov's chains. The main idea behind the method, described in this book, is to develop the original discrete optimization problems (or game models) in the space of randomized formulations, where the variables stand in for the distributions (mixed strategies or preferences) of the original discrete (pure) strategies in the use. The following suppositions are made: a finite state space, a limited action space, continuity of the probabilities and rewards associated with the actions, and a necessity for accessibility. These hypotheses lead to the existence of an optimal policy. The best course of action is always stationary. It is either simple (i.e., nonrandomized stationary) or composed of two nonrandomized policies, which is equivalent to randomly selecting one of two simple policies throughout each epoch by tossing a biased coin. As a bonus, the optimization procedure just has to repeatedly solve the time-average dynamic programming equation, making it theoretically feasible to choose the optimum course of action under the global restriction. In the ergodic cases the state distributions, generated by the corresponding transition equations, exponentially quickly converge to their stationary (final) values. This makes it possible to employ all widely used optimization methods (such as Gradient-like procedures, Extra-proximal method, Lagrange's multipliers, Tikhonov's regularization), including the related numerical techniques. In the book we tackle different problems and theoretical Markov models like controllable and ergodic Markov chains, multi-objective Pareto front solutions, partially observable Markov chains, continuous-time Markov chains, Nash equilibrium and Stackelberg equilibrium, Lyapunov-like function in Markov chains, Best-reply strategy, Bayesian incentive-compatible mechanisms, Bayesian Partially Observable Markov Games, bargaining solutions for Nash and Kalai-Smorodinsky formulations, multi-traffic signal-control synchronization problem, Rubinstein's non-cooperative bargaining solutions, the transfer pricing problem as bargaining.
Optimization and Learning: Third International Conference, OLA 2020, Cádiz, Spain, February 17–19, 2020, Proceedings (Communications in Computer and Information Science #1173)
by Bernabé Dorronsoro Patricia Ruiz El-Ghazali Talbi Juan Carlos de la Torre Daniel UrdaThis volume constitutes the refereed proceedings of the Third International Conference on Optimization and Learning, OLA 2020, held in Cádiz, Spain, in February 2020. The 23 full papers were carefully reviewed and selected from 55 submissions. The papers presented in the volume focus on the future challenges of optimization and learning methods, identifying and exploiting their synergies,and analyzing their applications in different fields, such as health, industry 4.0, games, logistics, etc.
Optimization and Optimal Control in a Nutshell (Engineering Optimization: Methods and Applications)
by Sudath Rohan MunasingheThis book concisely presents the optimization process and optimal control process with examples and simulations to help self-learning and better comprehension. It starts with function optimization and constraint inclusion and then extends to functional optimization using the calculus of variations. The development of optimal controls for continuous-time, linear, open-loop systems is presented using Lagrangian and Pontryagin-Hamiltonian methods, showing how to introduce the end-point conditions in time and state. The closed-loop optimal control for linear systems with a quadratic cost function, well-known as the linear quadratic regulator (LQR) is developed for both time-bound and time-unbounded conditions. Some control systems need to maximize performance alongside cost minimization. The Pontryagin's maximum principle is presented in this regard with clear examples that show the practical implementation of it. It is shown through examples how the maximum principle leads to control switching and Bang-Bang control in certain types of systems. The application of optimal controls in discrete-time open-loop systems with the quadratic cost is presented and then extended to the closed-loop control, which results in the model predictive control (MPC). Throughout the book, examples and Matlab simulation codes are provided for the learner to practice the contents in each section. The aligned lineup of content helps the learner develop knowledge and skills in optimal control gradually and quickly.
Optimization and Optimal Control in Automotive Systems
by Harald Waschl Ilya Kolmanovsky Maarten Steinbuch Luigi Del ReThis book demonstrates the use of the optimization techniques that are becoming essential to meet the increasing stringency and variety of requirements for automotive systems. It shows the reader how to move away from earlier approaches, based on some degree of heuristics, to the use of more and more common systematic methods. Even systematic methods can be developed and applied in a large number of forms so the text collects contributions from across the theory, methods and real-world automotive applications of optimization. Greater fuel economy, significant reductions in permissible emissions, new drivability requirements and the generally increasing complexity of automotive systems are among the criteria that the contributing authors set themselves to meet. In many cases multiple and often conflicting requirements give rise to multi-objective constrained optimization problems which are also considered. Some of these problems fall into the domain of the traditional multi-disciplinary optimization applied to system, sub-system or component design parameters and is performed based on system models; others require applications of optimization directly to experimental systems to determine either optimal calibration or the optimal control trajectory/control law. Optimization and Optimal Control in Automotive Systems reflects the state-of-the-art in and promotes a comprehensive approach to optimization in automotive systems by addressing its different facets, by discussing basic methods and showing practical approaches and specific applications of optimization to design and control problems for automotive systems. The book will be of interest both to academic researchers, either studying optimization or who have links with the automotive industry and to industrially-based engineers and automotive designers.
Optimization and Security Challenges in Smart Power Grids
by Vijay Pappu Marco Carvalho Panos M. PardalosThis book provides an overview of state-of-the-art research on "Systems and Optimization Aspects of Smart Grid Challenges. " The authors have compiled and integrated different aspects of applied systems optimization research to smart grids, and also describe some of its critical challenges and requirements. The promise of a smarter electricity grid could significantly change how consumers use and pay for their electrical power, and could fundamentally reshape the current Industry. Gaining increasing interest and acceptance, Smart Grid technologies combine power generation and delivery systems with advanced communication systems to help save energy, reduce energy costs and improve reliability. Taken together, these technologies support new approaches for load balancing and power distribution, allowing optimal runtime power routing and cost management. Such unprecedented capabilities, however, also present a set of new problems and challenges at the technical and regulatory levels that must be addressed by Industry and the Research Community.
Optimization-Based Energy Management for Multi-energy Maritime Grids (Springer Series on Naval Architecture, Marine Engineering, Shipbuilding and Shipping #11)
by Sidun Fang Hongdong WangThis open access book discusses the energy management for the multi-energy maritime grid, which is the local energy network installed in harbors, ports, ships, ferries, or vessels. The grid consists of generation, storage, and critical loads. It operates either in grid-connected or in islanding modes, under the constraints of both power system and transportation system. With full electrification, the future maritime grids, such as all-electric ships and seaport microgrids, will become “maritime multi-energy system” with the involvement of multiple energy, i.e., electrical power, fossil fuel, and heating/cooling power. With various practical cases, this book provides a cross-disciplinary view of the green and sustainable shipping via the energy management of maritime grids. In this book, the concepts and definitions of the multi-energy maritime grids are given after a comprehensive literature survey, and then the global and regional energy efficiency policies for the maritime transportation are illustrated. After that, it presents energy management methods under different scenarios for all-electric ships and electrified ports. At last, the future research roadmap are overviewed. The book is intended for graduate students, researchers, and professionals who are interested in the energy management of maritime transportation.
Optimization Based Model Using Fuzzy and Other Statistical Techniques Towards Environmental Sustainability
by Samsul Ariffin Abdul Karim Evizal Abdul Kadir Arbi Haza NasutionThis book explores key examples concerning the implementation of information technology and mathematical modeling to solve issues concerning environmental sustainability. The examples include using fuzzy weighted multivariate regression to predict the water quality index at Perak River in Malaysia; using wireless sensor networks (WSNs) for a remote river water pollution monitoring system; deriving biomass activated carbon from oil palm shell; and assessing the performance of a PV/T air solar collector. The book offers a valuable resource for all graduate students and researchers who are working in this rapidly growing area.