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Evolutionary Computation in Combinatorial Optimization, Gabriela Ochoa; Francisco Chicano


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Автор: Gabriela Ochoa; Francisco Chicano
Название:  Evolutionary Computation in Combinatorial Optimization
ISBN: 9783319164670
Издательство: Springer
Классификация:



ISBN-10: 3319164678
Обложка/Формат: Paperback
Страницы: 235
Вес: 0.35 кг.
Дата издания: 26.03.2015
Серия: Theoretical Computer Science and General Issues
Язык: English
Размер: 234 x 156 x 13
Основная тема: Computer Science
Подзаголовок: 15th European Conference, EvoCOP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings
Ссылка на Издательство: Link
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Поставляется из: Германии
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


Evolutionary Computation in Combinatorial Optimization

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: 9781.00 р.
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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.

Bioinspired Computation in Combinatorial Optimization

Автор: Frank Neumann; Carsten Witt
Название: Bioinspired Computation in Combinatorial Optimization
ISBN: 3642265847 ISBN-13(EAN): 9783642265846
Издательство: Springer
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Цена: 6986.00 р.
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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.

Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques

Автор: Irit Dinur; Klaus Jansen; Seffi Naor; Jos? Rolim
Название: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
ISBN: 3642036848 ISBN-13(EAN): 9783642036842
Издательство: Springer
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Цена: 18167.00 р.
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Описание: 12th International Workshop APPROX 2009 and 13th International Workshop RANDOM 2009 Berkeley CA USA. .

Combinatorial Optimization and Applications

Автор: T-H. Hubert Chan; Minming Li; Lusheng Wang
Название: Combinatorial Optimization and Applications
ISBN: 3319487485 ISBN-13(EAN): 9783319487489
Издательство: Springer
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Цена: 13696.00 р.
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Описание: This book constitutes the refereed proceedings of the 10th International Conference on Combinatorial Optimization and Applications, COCOA 2016, held in Hong Kong, China, in December 2016. The 60 full papers included in the book were carefully reviewed and selected from 122 submissions.

Combinatorial Optimization

Автор: Cerulli
Название: Combinatorial Optimization
ISBN: 3319455869 ISBN-13(EAN): 9783319455860
Издательство: Springer
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Цена: 9224.00 р.
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Описание: This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Symposium on Combinatorial Optimization, ISCO 2016, held in Vietri sul Mare, Italy, in May 2016. They present original research on all aspects of combinatorial optimization, such as algorithms and complexity;

Integer Programming and Combinatorial Optimization

Автор: Friedrich Eisenbrand; Jochen Koenemann
Название: Integer Programming and Combinatorial Optimization
ISBN: 3319592491 ISBN-13(EAN): 9783319592497
Издательство: Springer
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Цена: 9781.00 р.
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Описание: This book constitutes the refereed proceedings of the 19th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2017, held in Waterloo, IN, Canada, in June 2017.

Combinatorial Optimization and Graph Algorithms

Автор: Takuro Fukunaga; Ken-ichi Kawarabayashi
Название: Combinatorial Optimization and Graph Algorithms
ISBN: 9811061467 ISBN-13(EAN): 9789811061462
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Covering network designs, discrete convex analysis, facility location and clustering problems, matching games, and parameterized complexity, this book discusses theoretical aspects of combinatorial optimization and graph algorithms.

Evolutionary Computation in Combinatorial Optimization

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: 7685.00 р.
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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

Evolutionary Computation in Combinatorial Optimization

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: 6988.00 р.
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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.

Evolutionary Computation in Combinatorial Optimization

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: 10480.00 р.
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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.

Combinatorial optimization and applications

Название: Combinatorial optimization and applications
ISBN: 3642020259 ISBN-13(EAN): 9783642020254
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book constitutes the refereed proceedings of the Third International Conference on Combinatorial Optimization and Applications, COCOA 2009, held in Huangshan, China, in June 2009.

Iterative Methods in Combinatorial Optimization

Автор: Lau
Название: Iterative Methods in Combinatorial Optimization
ISBN: 1107007518 ISBN-13(EAN): 9781107007512
Издательство: Cambridge Academ
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Цена: 12830.00 р.
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Описание: This book describes a simple and powerful method that is iterative in essence and similarly useful in a variety of settings for exact and approximate optimization. The authors highlight the commonality and uses of this method to prove a variety of classical polyhedral results on matchings, trees, matroids and flows.


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