Evolutionary Computation in Combinatorial Optimization, Christian Blum; Gabriela Ochoa

Автор: Sundaram, Rangarajan K.
Название: A First Course in Optimization Theory
ISBN: 0521497701 ISBN-13(EAN): 9780521497701
Издательство: Cambridge Academ
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Цена: 45410.00 T
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Описание: This book, first published in 1996, introduces students to optimization theory and its use in economics and allied disciplines.

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

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: 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: Martin Middendorf; Christian Blum
Название: Evolutionary Computation in Combinatorial Optimization
ISBN: 3642371973 ISBN-13(EAN): 9783642371974
Издательство: Springer
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Цена: 42860.00 T
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Описание: A Hyper-heuristic with a Round Robin Neighbourhood.- A Multiobjective Approach Based on the Law of Gravity and Mass Interactions for Optimizing Networks.- A Multi-objective Feature Selection Approach Based on Binary PSO and Rough Set Theory.- A New Crossover for Solving Constraint Satisfaction Problems.- A Population-Based Strategic Oscillation Algorithm for Linear Ordering Problem with Cumulative Costs.- A Study of Adaptive Perturbation Strategy for Iterated Local Search.- Adaptive MOEA/D for QoS-Based Web Service Composition.- An Analysis of Local Search for the Bi-objective Bidimensional Knapsack Problem.- An Artificial Immune System Based Approach for Solving the Nurse Re-rostering Problem.- Automatic Algorithm Selection for the Quadratic Assignment Problem Using Fitness Landscape Analysis.- Balancing Bicycle Sharing Systems: A Variable Neighborhood Search Approach.- Combinatorial Neighborhood Topology Particle Swarm Optimization Algorithm for the Vehicle Routing Problem.- Dynamic Evolutionary Membrane Algorithm in Dynamic Environments.- From Sequential to Parallel Local Search for SAT.- Generalizing Hyper-heuristics via Apprenticeship Learning.- High-Order Sequence Entropies for Measuring Population Diversity in the Traveling Salesman Problem.- Investigating Monte-Carlo Methods on the Weak Schur Problem.- Multi-objective AI Planning: Comparing Aggregation and Pareto Approaches.- Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape.- Single Line Train Scheduling with ACO.- Solving Clique Covering in Very Large Sparse Random Graphs by a Technique Based on k-Fixed Coloring Tabu Search.- Solving the Virtual Network Mapping Problem with Construction Heuristics, Local Search and Variable Neighborhood Descent.- The Generate-and-Solve Framework Revisited: Generating by Simulated Annealing.

Автор: Jano van Hemert; Carlos Cotta
Название: Evolutionary Computation in Combinatorial Optimization
ISBN: 3540786031 ISBN-13(EAN): 9783540786030
Издательство: Springer
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Цена: 65210.00 T
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Описание: 8th European Conference EvoCOP 2008 Naples Italy March 26-28 2008 Proceedings.

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: 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: 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: Carlos Cotta; Jano van Hemert
Название: Recent Advances in Evolutionary Computation for Combinatorial Optimization
ISBN: 3642089739 ISBN-13(EAN): 9783642089732
Издательство: Springer
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Цена: 181670.00 T
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Описание: This cutting-edge volume presents recent advances in the area of metaheuristic combinatorial optimisation, with a special focus on evolutionary computation methods. Moreover, it addresses local search methods and hybrid approaches.