Evolutionary Computation for Dynamic Optimization Problems, Shengxiang Yang; Xin Yao

Автор: Shengxiang Yang; Xin Yao
Название: Evolutionary Computation for Dynamic Optimization Problems
ISBN: 3642448437 ISBN-13(EAN): 9783642448430
Издательство: Springer
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Цена: 174130.00 T
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Описание: This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems.

Автор: Manuel Barros; Jorge Guilherme; Nuno Horta
Название: Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques
ISBN: 3642263232 ISBN-13(EAN): 9783642263231
Издательство: Springer
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Цена: 158380.00 T
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Описание: Transistor-level design for complex mixed-signal systems-on-chip remains difficult to automate. This book shows how a modified genetic algorithm kernel can improve efficiency in the analog IC design cycle and includes a worked example of the method.

Автор: Oliver Kramer
Название: A Brief Introduction to Continuous Evolutionary Optimization
ISBN: 3319034219 ISBN-13(EAN): 9783319034218
Издательство: Springer
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Цена: 60940.00 T
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Описание: This book introduces heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. It presents heuristic extensions that allow optimization in constrained, multimodal and multi-objective solution spaces.

Автор: Bin Hu; Manuel L?pez-Ib??ez
Название: Evolutionary Computation in Combinatorial Optimization
ISBN: 3319554522 ISBN-13(EAN): 9783319554525
Издательство: Springer
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Цена: 51230.00 T
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Описание: A Computational Study of Neighborhood Operators for Job-shop Scheduling Problems with Regular Objectives.- A Genetic Algorithm for Multi-Component Optimization Problems: the Case of the Travelling Thief Problem.- A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search.- A Memetic Algorithm to Maximise the Employee Substitutability in Personnel Shift Scheduling.- Construct, Merge, Solve and Adapt versus Large Neighborhood Search for Solving the Multi-Dimensional Knapsack Problem: Which One Works Better When.- Decomposing SAT Instances with Pseudo Backbones.- Efficient Consideration of Soft Time Windows in a Large Neighborhood Search for the Districting and Routing Problem for Security Control.- Estimation of Distribution Algorithms for the Firefighter Problem.- LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows.- Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO.- Optimizing Charging Station Locations for Electric Car-Sharing Systems.- Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier.- Sparse, Continuous Policy Representations for Uniform Online Bin Packing via Regression of Interpolants.- The Weighted Independent Domination Problem: ILP Model and Algorithmic

Автор: Manuel Barros; Jorge Guilherme; Nuno Horta
Название: Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques
ISBN: 3642123457 ISBN-13(EAN): 9783642123450
Издательство: Springer
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Цена: 158380.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Transistor-level design for complex mixed-signal systems-on-chip remains difficult to automate. This book shows how a modified genetic algorithm kernel can improve efficiency in the analog IC design cycle and includes a worked example of the method.

Автор: Daniel Ashlock
Название: Evolutionary Computation for Modeling and Optimization
ISBN: 1441919694 ISBN-13(EAN): 9781441919694
Издательство: Springer
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Цена: 67030.00 T
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Описание:

Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets.

Автор: Ant?nio Gaspar-Cunha; Carlos Henggeler Antunes; Ca
Название: Evolutionary Multi-Criterion Optimization
ISBN: 3319158910 ISBN-13(EAN): 9783319158914
Издательство: Springer
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Цена: 81990.00 T
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Описание: This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 held in Guimaraes, Portugal in March/April 2015.

Автор: Shengxiang Yang; Yew-Soon Ong; Yaochu Jin
Название: Evolutionary Computation in Dynamic and Uncertain Environments
ISBN: 3642080650 ISBN-13(EAN): 9783642080654
Издательство: Springer
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Цена: 243800.00 T
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Описание: Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.

Автор: M.C. Bhuvaneswari
Название: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
ISBN: 8132219570 ISBN-13(EAN): 9788132219576
Издательство: Springer
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Цена: 130430.00 T
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Описание: This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design.

Автор: Ant?nio Gaspar-Cunha; Carlos Henggeler Antunes; Ca
Название: Evolutionary Multi-Criterion Optimization
ISBN: 331915933X ISBN-13(EAN): 9783319159331
Издательство: Springer
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Цена: 59630.00 T
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Описание: This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 held in Guimaraes, Portugal in March/April 2015.

Автор: Chi-Keong Goh; Kay Chen Tan
Название: Evolutionary Multi-objective Optimization in Uncertain Environments
ISBN: 3642101135 ISBN-13(EAN): 9783642101137
Издательство: Springer
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Цена: 139750.00 T
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Описание: The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. The book is intended for a wide readership.

Автор: Heike Trautmann; G?nter Rudolph; Kathrin Klamroth;
Название: Evolutionary Multi-Criterion Optimization
ISBN: 3319541560 ISBN-13(EAN): 9783319541563
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book constitutes the refereed proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 held in Munster, Germany in March 2017. The EMO 2017 aims to discuss all aspects of EMO development and deployment, including theoretical foundations; parallel EMO models; EMO algorithm implementations.