Evolutionary Computation in Combinatorial Optimization, Liefooghe
Автор: Shengxiang Yang; Xin Yao Название: Evolutionary Computation for Dynamic Optimization Problems ISBN: 3642448437 ISBN-13(EAN): 9783642448430 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems.
Автор: Carlos Cotta; Peter I. Cowling Название: Evolutionary Computation in Combinatorial Optimization ISBN: 3642010083 ISBN-13(EAN): 9783642010088 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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 Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Gabriela Ochoa; Francisco Chicano Название: Evolutionary Computation in Combinatorial Optimization ISBN: 3319164678 ISBN-13(EAN): 9783319164670 Издательство: Springer Рейтинг: Цена: 6708.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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 Рейтинг: Цена: 6988.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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.
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: 3642384153 ISBN-13(EAN): 9783642384158 Издательство: Springer Рейтинг: Цена: 32652.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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 Рейтинг: Цена: 10055.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets.
Lots of applications and test problems, including a biotechnology chapter.
Автор: Bin Hu; Manuel L?pez-Ib??ez Название: Evolutionary Computation in Combinatorial Optimization ISBN: 3319554522 ISBN-13(EAN): 9783319554525 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Arnaud Liefooghe; Lu?s Paquete Название: Evolutionary Computation in Combinatorial Optimization ISBN: 3030167100 ISBN-13(EAN): 9783030167103 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 19th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2019, held as part of Evo* 2019, in Leipzig, Germany, in April 2019, co-located with the Evo* 2019 events EuroGP, EvoMUSART and EvoApplications.The 14 revised full papers presented were carefully reviewed and selected from 37 submissions. The papers cover a wide spectrum of topics, ranging from the foundations of evolutionary computation algorithms and other search heuristics to their accurate design and application to both single- and multi-objective combinatorial optimization problems. Fundamental and methodological aspects deal with runtime analysis, the structural properties of fitness landscapes, the study of metaheuristics core components, the clever design of their search principles, and their careful selection and configuration. Applications cover domains such as scheduling, routing, partitioning and general graph problems.
Автор: Frank Neumann; Carsten Witt Название: Bioinspired Computation in Combinatorial Optimization ISBN: 3642265847 ISBN-13(EAN): 9783642265846 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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