Evolutionary Computation in Combinatorial Optimization, Bin Hu; Manuel L?pez-Ib??ez

Автор: Carlos Cotta; Peter I. Cowling
Название: Evolutionary Computation in Combinatorial Optimization
ISBN: 3642010083 ISBN-13(EAN): 9783642010088
Издательство: Springer
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Цена: 65210.00 T
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Описание: Constitutes the refereed proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2009, held in Tubingen, Germany, in April 2009. This work contains papers that discuss developments and applications in metaheuristics.

Автор: Peter I. Cowling; Peter Merz
Название: Evolutionary Computation in Combinatorial Optimization
ISBN: 3642121381 ISBN-13(EAN): 9783642121388
Издательство: Springer
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Цена: 69870.00 T
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Описание: Constitutes the refereed proceedings of the 10th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2010, held in Instanbul, Turkey, in April 2010. This book discusses developments and applications in metaheuristics.

Автор: Frank Neumann; Carsten Witt
Название: Bioinspired Computation in Combinatorial Optimization
ISBN: 3642265847 ISBN-13(EAN): 9783642265846
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book shows how runtime behavior can be analyzed in a rigorous way and for combinatorial optimization in particular. It presents well-known problems such as minimum spanning trees, shortest paths, maximum matching, and covering and scheduling problems.

Автор: Korte, Bernhard, Vygen, Jens
Название: Combinatorial Optimization (algorithms and Combinatorics 21) 5th ed.
ISBN: 3642244874 ISBN-13(EAN): 9783642244872
Издательство: Springer
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Цена: 60510.00 T
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Описание: This comprehensive textbook on combinatorial optimization places special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It is based on numerous courses on combinatorial optimization and specialized topics, mostly at graduate level. This book reviews the fundamentals, covers the classical topics (paths, flows, matching, matroids, NP-completeness, approximation algorithms) in detail, and proceeds to advanced and recent topics, some of which have not appeared in a textbook before. Throughout, it contains complete but concise proofs, and also provides numerous exercises and references. This fifth edition has again been updated, revised, and significantly extended, with more than 60 new exercises and new material on various topics, including Cayley's formula, blocking flows, faster b-matching separation, multidimensional knapsack, multicommodity max-flow min-cut ratio, and sparsest cut. Thus, this book represents the state of the art of combinatorial optimization.

Автор: Gabriela Ochoa; Francisco Chicano
Название: Evolutionary Computation in Combinatorial Optimization
ISBN: 3319164678 ISBN-13(EAN): 9783319164670
Издательство: Springer
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Цена: 44720.00 T
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Описание: A Biased Random-Key Genetic Algorithm for the Cloud Resource Management Problem.- A Computational Comparison of Different Algorithms for Very Large p-median Problems.- A New Solution Representation for the Firefighter Problem.- A Variable Neighborhood Search Approach for the Interdependent Lock Scheduling Problem.- A Variable Neighborhood Search for the Generalized Vehicle Routing Problem with Stochastic Demands.- An Iterated Local Search Algorithm for Solving the Orienteering Problem with Time Windows.- Analysis of Solution Quality of a Multi objective Optimization-Based Evolutionary Algorithm for Knapsack Problem.- Evolving Deep Recurrent Neural Networks Using Ant Colony Optimization.- Hyper-heuristic Operator Selection and Acceptance Criteria.- Improving the Performance of the Germinal Center Artificial Immune System Using ε-Dominance: A Multi-objective Knapsack Problem.- Mixing Network Extremal Optimization for Community Structure Detection.- Multi-start Iterated Local Search for the Mixed Fleet Vehicle Routing Problem with Heterogeneous Electric Vehicles.- On the Complexity of Searching the Linear Ordering Problem Neighborhoods.- Runtime Analysis of (1 + 1) Evolutionary Algorithm Controlled with Q-learning Using Greedy Exploration Strategy on ONEMAX+ZEROMAX Problem.- The New Memetic Algorithm HEAD for Graph Coloring: An Easy Way for Managing Diversity.- The Sim-EA Algorithm with Operator Auto adaptation for the Multi objective Firefighter Problem.- True Pareto Fronts for Multi-objective AI Planning Instances.- Upper and Lower Bounds on Unrestricted Black-Box Complexity of JUMPn, l.- Using Local Search to Evaluate Dispatching Rules in Dynamic Job Shop Scheduling

Автор: Francisco Chicano; Bin Hu; Pablo Garc?a-S?nchez
Название: Evolutionary Computation in Combinatorial Optimization
ISBN: 3319306979 ISBN-13(EAN): 9783319306971
Издательство: Springer
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Цена: 46590.00 T
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Описание: A Hybrid Constructive Mat-Heuristic Algorithm for The Heterogeneous Vehicle Routing Problem with Simultaneous Pick-up and Delivery.- A Property Preserving Method for Extending a Single-Objective Problem Instance to Multiple Objectives with Specific Correlations.- An Evolutionary Approach to the Full Optimization of the Traveling Thief Problem.- Construct, Merge, Solve & Adapt: Application to the Repetition-Free Longest Common Subsequence Problem.- Deconstructing the Big Valley Search Space Hypothesis.- Determining the Difficulty of Landscapes by PageRank Centrality in Local Optima Networks.- Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization.- Evaluating Hyperheuristics and Local Search Operators for Periodic Routing Problems.- Evolutionary Algorithms for Finding Short Addition Chains: Going the Distance.- Experimental Evaluation of Two Approaches to Optimal Recombination for Permutation Problems.- Hyperplane Elimination for Quickly Enumerating Local Optima.- Limits to Learning in Reinforcement Learning Hyperheuristics.- Modifying Colourings between Time-Steps to Tackle Changes in Dynamic Random Graphs.- Particle Swarm Optimisation with Sequence-Like Indirect Representation for Web Service Composition.- Particle Swarm Optimization for Multi-Objective Web Service Location Allocation.- Sim-EDA: A Multipopulation Estimation of Distribution Algorithm Based on Problem Similarity.- Solving the Quadratic Assignment Problem with Cooperative Parallel Extremal Optimization.

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: 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: Shengxiang Yang; Xin Yao
Название: Evolutionary Computation for Dynamic Optimization Problems
ISBN: 3642384153 ISBN-13(EAN): 9783642384158
Издательство: Springer
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Цена: 217680.00 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: 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: 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
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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: Chandra Chekuri; Klaus Jansen; Jos? D.P. Rolim; Lu
Название: Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques
ISBN: 3540282394 ISBN-13(EAN): 9783540282396
Издательство: Springer
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Цена: 93160.00 T
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Описание: Contains 41 reviewed papers, selected by the two program committees from a total of 101 submissions. Among the issues addressed are design and analysis of approximation algorithms, hardness of approximation, small space and data streaming algorithms, sub-linear time algorithms, embeddings and metric space methods, and more.