Modern Music-Inspired Optimization Algorithms for Electric Power Systems: Modeling, Analysis and Practice, Kiani-Moghaddam Mohammad, Shivaie Mojtaba, Weinsier Philip D.
Автор: Resener Mariana, Rebennack Steffen, Pardalos Panos Название: Handbook of Optimization in Electric Power Distribution Systems ISBN: 3030361144 ISBN-13(EAN): 9783030361143 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This handbook gathers state-of-the-art research on optimization problems in power distribution systems, covering classical problems as well as the challenges introduced by distributed power generation and smart grid resources.
Описание: Presenting ways of using AI optimization techniques to operate and control electric power systems, this book is full of practical applications and examples and features, among other methods, functional analysis, simulated annealing and Tabu-search.
Автор: Karl Frauendorfer; Hans Glavitsch; Rainer Bacher Название: Optimization in Planning and Operation of Electric Power Systems ISBN: 3790807184 ISBN-13(EAN): 9783790807189 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Permanently increasing requirements in power supply necessitate efficient control of electric power systems. This work represents a state-of-the-art of mathematical programming methodologies, unit commitment, optimal power flow and their applications in power system control.
Автор: Omid Bozorg-Haddad Название: Advanced Optimization by Nature-Inspired Algorithms ISBN: 981135345X ISBN-13(EAN): 9789811353451 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.
Автор: Xin-She Yang Название: Nature-Inspired Algorithms and Applied Optimization ISBN: 3319884654 ISBN-13(EAN): 9783319884653 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Поставка под заказ.
Описание: This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.
Описание: A modern and unique treatment of process optimization which presents a thorough exposition of applications and algorithms in sufficient detail for practical use. A perfect tool for advanced undergraduate and graduate courses in chemical and biochemical engineering.
Описание: Preface.- Introduction.- Simulated Annealing.- Optimization by Recurrent Neural Networks.- Genetic Algorithms and Genetic Programming.- Evolutionary Strategies.- Differential Evolution.- Estimation of Distribution Algorithms.- Mimetic Algorithms.- Topics in EAs.- Particle Swarm Optimization.- Artificial Immune Systems.- Ant Colony Optimization.- Tabu Search and Scatter Search.- Bee Metaheuristics.- Harmony Search.- Biomolecular Computing.- Quantum Computing.- Other Heuristics-Inspired Optimization Methods.- Dynamic, Multimodal, and Constraint-Satisfaction Optimizations.- Multiobjective Optimization.- Appendix 1: Discrete Benchmark Functions.- Appendix 2: Test Functions.- Index.
Автор: Maitine Bergounioux, ?douard Oudet, Martin Rumpf, Название: Topological Optimization and Optimal Transport: In the Applied Sciences ISBN: 3110439263 ISBN-13(EAN): 9783110439267 Издательство: Walter de Gruyter Рейтинг: Цена: 26024.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
By discussing topics such as shape representations, relaxation theory and optimal transport, trends and synergies of mathematical tools required for optimization of geometry and topology of shapes are explored. Furthermore, applications in science and engineering, including economics, social sciences, biology, physics and image processing are covered.
Contents Part I
Geometric issues in PDE problems related to the infinity Laplace operator
Solution of free boundary problems in the presence of geometric uncertainties
Distributed and boundary control problems for the semidiscrete Cahn-Hilliard/Navier-Stokes system with nonsmooth Ginzburg-Landau energies
High-order topological expansions for Helmholtz problems in 2D
On a new phase field model for the approximation of interfacial energies of multiphase systems
Optimization of eigenvalues and eigenmodes by using the adjoint method
Discrete varifolds and surface approximation
Part II
Weak Monge-Ampere solutions of the semi-discrete optimal transportation problem
Optimal transportation theory with repulsive costs
Wardrop equilibria: long-term variant, degenerate anisotropic PDEs and numerical approximations
On the Lagrangian branched transport model and the equivalence with its Eulerian formulation
On some nonlinear evolution systems which are perturbations of Wasserstein gradient flows
Pressureless Euler equations with maximal density constraint: a time-splitting scheme
Convergence of a fully discrete variational scheme for a thin-film equatio
Interpretation of finite volume discretization schemes for the Fokker-Planck equation as gradient flows for the discrete Wasserstein distance
Автор: Mohammad Kiani-Moghaddam; Mojtaba Shivaie; Philip Название: Modern Music-Inspired Optimization Algorithms for Electric Power Systems ISBN: 3030120430 ISBN-13(EAN): 9783030120436 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
In today’s world, with an increase in the breadth and scope of real-world engineering optimization problems as well as with the advent of big data, improving the performance and efficiency of algorithms for solving such problems has become an indispensable need for specialists and researchers. In contrast to conventional books in the field that employ traditional single-stage computational, single-dimensional, and single-homogeneous optimization algorithms, this book addresses multiple newfound architectures for meta-heuristic music-inspired optimization algorithms. These proposed algorithms, with multi-stage computational, multi-dimensional, and multi-inhomogeneous structures, bring about a new direction in the architecture of meta-heuristic algorithms for solving complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data. The architectures of these new algorithms may also be appropriate for finding an optimal solution or a Pareto-optimal solution set with higher accuracy and speed in comparison to other optimization algorithms, when feasible regions of the solution space and/or dimensions of the optimization problem increase.
This book, unlike conventional books on power systems problems that only consider simple and impractical models, deals with complicated, techno-economic, real-world, large-scale models of power systems operation and planning. Innovative applicable ideas in these models make this book a precious resource for specialists and researchers with a background in power systems operation and planning.
Provides an understanding of the optimization problems and algorithms, particularly meta-heuristic optimization algorithms, found in fields such as engineering, economics, management, and operations research;Enhances existing architectures and develops innovative architectures for meta-heuristic music-inspired optimization algorithms in order to deal with complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data;Addresses innovative multi-level, techno-economic, real-world, large-scale, computational-logical frameworks for power systems operation and planning, and illustrates practical training on implementation of the frameworks using the meta-heuristic music-inspired optimization algorithms.
Описание: Integer linear programming is a versatile modeling and optimization technique with potential to transform biological computation. This hands-on text, designed for students, researchers, and professionals in both biology and computational fields, demonstrates applications in genomics, RNA and protein folding, DNA sequencing, phylogenetics, and more.
Описание: The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems.The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.
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